Carlos's Debrief

June 18, 2026 04:00
49ArXiv Papers
29Web Findings
78Total Sources
Topics searched: Artificial Intelligence Machine Learning Large Language Models Security & Cybersecurity Cryptography Zero Knowledge Quantum Computing Crypto & Blockchain AI Agents & Reasoning AI Safety & Alignment
June 18, 2026 04:00 — Curated by Hermes Research Scout

⚡ Quick Summary

📰 News Headlines

🗡️ Relevant to your Katana work 3

📄 ArXiv Papers

🧠 Code / Injection / Malicious 5

OpenAnt: LLM-Powered Vulnerability Discovery Through Code Decomposition, Adversarial Verification, and Dynamic Testing [28]
Nahum Korda, Gadi Evron
Automated vulnerability discovery in large codebases remains challenging: traditional static analysis produces high false-positive rates, while dynamic approaches such as fuzzing require substantial…
cs.CRcs.LG
Compute-Budgeted Exploitability Evidence Graphs for Prospective Vulnerability Triage [31]
Faruk Alpay, Taylan Alpay
Defenders cannot patch every newly disclosed vulnerability at once, so exploitability prediction must be evaluated prospectively rather than retrospectively. We study compute-budgeted vulnerability…
cs.CR
PhantomSkill: Malicious Code Injection in Agent Skill Ecosystems [27]
Yu-Ting Lin, Chia-Mu Yu
Agent skills allow LLM-based coding agents to acquire domain-specific capabilities from third-party packages, but they also introduce a new supply-chain attack surface. We present PhantomSkill, an…
cs.CR
CodeSentinel: A Three-Layer Defense Against Indirect Prompt Injection in Code Contexts [26]
Po-Han Cheng, Chia-Mu Yu, Ying-Dar Lin, Yu-Sung Wu, Wei-Bin Lee
Code large language models increasingly retrieve external code context from repositories, documentation, issue threads, and coding-agent environments, creating an indirect prompt-injection surface…
cs.CR
PYPILINE: Malicious PyPI Package Detection via Suspicious API Knowledge and Agent Workflow [32]
Siyuan Pang, Zhengwei Jiang, Yepeng Yao, Zijing Fan, Haozhe Li, Baoxu Liu
The detection of malicious PyPI packages is crucial for maintaining the security of the open source software supply chain. Existing methods, which primarily rely on rules or traditional machine…
cs.CR

🧠 Dexterous / Manipulation / Reasoning 4

Does VLA Even Know the Basics? Measuring Commonsense and World Knowledge Retention in Vision-Language-Action Models [17]
Nikita Kachaev, Andrey Moskalenko, Matvey Skripkin, Nikita Kurlaev, Daria Pugacheva, Albina Burlova, Mikhail Kolosov, Denis Shepelev, Andrey Kuznetsov, Elena Tutubalina, Aleksandr I. Panov, Alexey K. Kovalev, Vlad Shakhuro
Embodied Vision-Language-Action (VLA) models are typically obtained by fine-tuning powerful pretrained VLMs on robotics data, yet it is unclear how much commonsense and factual knowledge they retain…
cs.LGcs.RO
Native Active Perception as Reasoning for Omni-Modal Understanding [20]
Zhenghao Xing, Ruiyang Xu, Yuxuan Wang, Jinzheng He, Ziyang Ma, Qize Yang, Yunfei Chu, Jin Xu, Junyang Lin, Chi-Wing Fu, Pheng-Ann Heng
Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to grow with video…
cs.CVcs.CLcs.SD
Zero-Shot Long-Horizon Dexterous Manipulation via Multi-View 3D-Grounded VLM Reasoning [19]
Jisoo Kim, Sangwon Baik, Taeksoo Kim, Sungjoo Kim, Junyoung Lee, Mingi Choi, Hanbyul Joo
We present a zero-shot framework for long-horizon dexterous manipulation that grounds language instructions into executable 3D task plans from calibrated multi-view RGB images. Rather than training…
cs.RO
Do as I Do: Dexterous Manipulation Data from Everyday Human Videos [42]
Bhawna Paliwal, Haritheja Etukuru, William Liang, Pieter Abbeel, Nur Muhammad Mahi Shafiullah, Jitendra Malik
How can we scalably generate data for robotic manipulation, especially on human-like platforms such as dexterous multi-fingered hands? Learning from human videos has recently emerged as a likely…
cs.ROcs.CV

🧠 X+slides / Benchmarking / Audience-conditioned 2

Beyond the Current Observation: Evaluating Multimodal Large Language Models in Controllable Non-Markov Games [21]
Shengyuan Ding, Xilin Wei, Xinyu Fang, Haodong Duan, Dahua Lin, Jiaqi Wang, Yuhang Zang
Deploying multimodal foundation models as closed-loop policies increasingly requires conditioning actions on observations that are no longer visible. However, existing benchmarks either expose the…
cs.CV
X+Slides: Benchmarking Audience-Conditioned Slide Generation [10]
Haodong Chen, Xuanhe Zhou, Wei Zhou, Xinyue Shao, Yanbing Zhu, Bo Wang, Jiawei Hong, Anya Jia, Fan Wu
Automatically generating slide decks from source documents is an important application of large language models (LLMs). Existing benchmarks primarily assess slide completeness and technical depth,…
cs.AI

🧠 Structured / Lattices / Their 2

Perfect Sphere Packing In The Boolean Space [35]
Tigran Soghomonyan, Zhirayr Margaryan
Perfect sphere packing in the Boolean space is a fundamental and complex problem with significant implications for coding theory, cryptography, and discrete mathematics. The classical solution to the…
math.COcs.DMcs.IT
Structured lattices and their applications to security [34]
Lenny Fukshansky, Camilla Hollanti, Rahinatou Y. Njah Nchiwo
Euclidean lattices are an interesting object of study in many regards and can have a rich structure arising from various constructions, e.g., from number field extensions. A particularly interesting…
math.NTcs.CRcs.IT

🧠 Ubp2 / Uncertainty-balanced / Preference 1

UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning [1]
Mohamed Nabail, Leo Cheng, Jingmin Wang, Nicholas Rhinehart
Preference-based RL provides an approach to learning reward models from pairwise comparisons of behaviors, bypassing the need for explicit reward design. However, existing methods typically rely on…
cs.LGcs.AIcs.RO

🧠 Rethinking / Reward / Supervision 1

Rethinking Reward Supervision: Rubric-Conditioned Self-Distillation [2]
Siyi Gu, Jialin Chen, Sophia Zhou, Arman Cohan, Rex Ying
Post-training of reasoning language models is commonly driven by supervised distillation and reinforcement learning with verifiable rewards. Distillation often relies on chain-of-thought annotations…
cs.AIcs.CL

🧠 Reference-driven / Multi-speaker / Audio 1

Reference-Driven Multi-Speaker Audio Scene Generation from In-the-Wild Priors [3]
Michael Finkelson, Daniel Segal, Eitan Richardson, Shahar Armon, Nani Goldring, Poriya Panet, Nir Zabari, Benjamin Brazowski, Or Patashnik, Yoav HaCohen
Existing multi-speaker dialogue systems bind speakers to utterances through structured supervision: per-turn tags, multi-stream transcriptions, or learnable speaker embeddings. These systems operate…
cs.SDcs.AIcs.CV

🧠 Data / Agents / Intelligence 1

Data Intelligence Agents: Interpreting, Modeling, and Querying Enterprise Data via Autonomous Coding Agents [4]
Anoushka Vyas, Aarushi Dhanuka, Sina Khoshfetrat Pakazad, Henrik Ohlsson
Production data integration is bottlenecked by repeated, lossy handoffs between data owners, engineers, and analysts who must collaboratively discover, structure, and query enterprise data. We…
cs.MAcs.AIcs.DB

🧠 Explaining / Attention / Program 1

Explaining Attention with Program Synthesis [5]
Amiri Hayes, Belinda Li, Jacob Andreas
A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descriptions. In this paper, we propose an approach for…
cs.LGcs.AI

🧠 Social / Correct / Yourself 1

Correct Yourself, Keep My Trust: How Self-Correction and Social Connection Shape Credibility in Social Chatbots [6]
Biswadeep Sen, Yi-Chieh Lee
When social chatbots make mistakes, and they do, how they recover determines whether users trust them again. Social chatbots are increasingly integrated into everyday life, yet they remain prone to…
cs.HCcs.AIcs.CY

🧠 Nesycat / Torch / Differentiable 1

NeSyCat Torch: A Differentiable Tensor Implementation of Categorical Semantics for Neurosymbolic Learning [7]
Daniel Romero Schellhorn, Till Mossakowski, Björn Gehrke
Neurosymbolic semantics is fragmented: classical, fuzzy, probabilistic and neural systems each define truth by their own inductive rules. NeSyCat, extending ULLER, subsumes them under a single…
cs.AIcs.LGcs.LO

🧠 Trade-offs / Medical / Llm 1

Trade-offs in Medical LLM Adaptation: An Empirical Study in French QA [8]
Ikram Belmadani, Oumaima El Khettari, Carlos Ramisch, Frederic Bechet, Richard Dufour, Benoit Favre
The development of large language models (LLMs) has led to an increased focus on their adaptation to specialized domains and languages, yet the effectiveness of domain adaptation strategies remains…
cs.CLcs.AI

🧠 Multi-domain / Benchmark / Detecting 1

A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-2 [9]
Yijin Wang, Shuyi Wang, Wenhan Zhang, Yuqi Ouyang
Text-rich images often contain privacy-sensitive, transactional, or decision-relevant information. As recent multimodal image generation models become increasingly capable of synthesizing realistic…
cs.CVcs.AI

🧠 Freeing / Law / Locus 1

Freeing the Law with LOCUS: A Local Ordinance Corpus for the United States [11]
Denis Peskoff, Joe Barrow, Christopher Vu, Diag Davenport
Progress in legal AI increasingly depends on access to authoritative legal text at scale. Yet one of the most consequential layers of American law remains largely absent from existing…
cs.CLcs.CYcs.LG

🧠 Catalog / Chandra-gaia / Counterparts 1

The Chandra-Gaia Catalog of Counterparts: Resolving ambiguous Gaia matches to X-ray sources in the Chandra Source Catalog using Machine Learning [12]
V. Samuel Pérez-Díaz, Vinay L. Kashyap, Joshua D. Ingram, David Fouhey, Juan Rafael Martínez-Galarza, Pavlos Protopapas, Jeremy J. Drake, Dong-Woo Kim, Cecilia Garraffo
We present a framework to cross-match sources from the Chandra Source Catalog (CSC v2.1) with optical sources from Gaia Data Release 3. Unlike purely spatial approaches, we use source properties such…
astro-ph.IMcs.LG

🧠 Diffusion-proof / Recipe / Formal 1

Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation [13]
Ruida Wang, Rui Pan, Pengcheng Wang, Shizhe Diao, Tong Zhang
Enhancing the formal math reasoning capabilities of Large Language Models (LLMs) has become a key focus in both mathematical and computer science communities in recent years. While significant…
cs.LG

🧠 P-k-gcn / Physics-augmented / Koopman-enhanced 1

P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution [14]
Xizhuo, Zhang, Zekai Wang, Fei Liu, Bing Yao
High-fidelity simulation of spatiotemporal dynamics is computationally prohibitive, necessitating efficient super-resolution techniques to reconstruct high-resolution data from coarse-grained inputs.…
cs.LG

🧠 Optimal / Scenario / Design 1

Optimal scenario design for climate emulation [15]
Christopher B. Womack, Shahine Bouabid, Andrei Sokolov, Popat Salunke, Glenn Flierl, Sebastian D. Eastham, Noelle E. Selin
As deep learning for physical systems continues to grow in popularity, efforts to improve generalizability have primarily focused on designing architectures that embed physical constraints. However,…
physics.ao-phcs.LG

🧠 Confidence / Not / Reliability 1

Confidence is Not Reliability: Rethinking MC Dropout in Brain Tumour Segmentation [16]
Xin Ci Wong, Duygu Sarikaya, Kieran Zucker, Marc De Kamps, Nishant Ravikumar
Glioma segmentation in multiparametric MRI is a critical component of treatment planning. A segmentation model that fails silently on treatment-critical sub-regions represents a patient safety risk…
cs.CVcs.LG

🧠 Risk / Stratification / Icu 1

Risk Stratification for ICU Delirium using Pervasive Ambient Sensing Information [18]
Jiaqing Zhang, Sabyasachi Bandyopadhyay, Miguel Contreras, Jessica Sena, Yuanfang Ren, Andrea Davidson, Ziyuan Guan, Tezcan Ozrazgat-Baslanti, Subhash Nerella, Azra Bihorac, Parisa Rashidi
Delirium is a common and serious complication in the Intensive Care Unit (ICU), associated with increased morbidity, prolonged hospital stays, and higher healthcare costs. Despite its prevalence,…
cs.LG

🧠 Constraints / Cosmic / Strings 1

Constraints on Cosmic Strings from the Curl-Mode CMB Lensing Power Spectrum measured by ACT DR6 [22]
A. I. Lonappan, K. Ramesh, T. Namikawa, F. J. Qu, B. Keating
A network of cosmic strings is one of the few well-motivated cosmological sources of vector and tensor metric perturbations on the largest observable scales. Such perturbations imprint a…
astro-ph.COgr-qchep-ph

🧠 User / Simulators / Turing 1

Learning User Simulators with Turing Rewards [23]
Yingshan Susan Wang, Cedegao E. Zhang, Linlu Qiu, Zexue He, Pengyuan Li, Alex Pentland, Roger P. Levy, Yoon Kim
Learning to simulate human users in interactive settings could advance the training of agent assistants, evaluation of personalization systems, research in the social sciences, and more. Existing…
cs.CL

🧠 Sparse-dense / Flight / Copy-based 1

Sparse-dense flight copy-based interactive mechanism to airline integrated with cruise speed control [24]
Jiajin Lin, Jianlin Jiang, Yan Gu, Yuzhen Guo, Cheng-Lung Wu
Flight recovery, aircraft rerouting, and passenger reallocation are critical in airline recovery. To preserve their interdependence that is neglected by the regular sequential recovery, we consider…
math.OC

🧠 Topological / Spectral / Form 1

Topological spectral form factor reveals emergent non-Hermitian single-particle $\mathcal{PT}$ transitions from many-body quantum chaos [25]
Daniel Harkin, Chun Y. Leung, Amos Chan
In equilibrium physics, topological defect insertions in quantum and classical partition functions provide non-perturbative probes of phase transitions beyond local observables. In non-equilibrium…
cond-mat.stat-mechhep-thnlin.CD

🧠 Giskard / Byzantine / Robust 1

Giskard : Byzantine Robust and Confidential Aggregation for Large-Scale Decentralized Learning [29]
Ousmane Touat, César Sabater, Mohamed Maouche, Sonia Ben Mokhtar
Dealing simultaneously with confidentiality and Byzantine behaviors in decentralized learning is a challenging problem. Indeed, in decentralized learning, clients train a machine learning model while…
cs.CRcs.LG

🧠 Quantifying / Compromise / Risk 1

Quantifying Compromise Risk in Exceptional Access Architectures Under Sparse and Indirect Evidence [30]
Alan Woodward
Lawful exceptional access (EA) systems hold the cryptographic keys that decrypt protected communications for authorised parties. The debate over their risks has been long and qualitative, complicated…
cs.CRcs.CY

🧠 Cheri-d / Secure / Efficient 1

CHERI-D: Secure and efficient inline object ID for CHERI temporal memory safety [33]
Yuecheng Wang, Jonathan Woodruff, Alfredo Mazzinghi, Peter Rugg, Samuel W. Stark, Alexandre Joannou, Robert N. M. Watson, Simon W. Moore
We propose CHERI-D, an architectural extension to CHERI that supports efficient temporal memory safety. Efficient memory safety is an increasing priority for programming languages, operating systems,…
cs.ARcs.CR

🧠 Mids / Detecting / Stealthy 1

MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mamba [36]
Qiqi Liu, Runhan Song, Lei Cui, Heng Zhang, Yuyan Sun, Limin Sun
The Controller Area Network (CAN) protocol is the primary communication standard for Electronic Control Units (ECUs) in modern vehicles, but its lack of encryption and authentication exposes it to a…
cs.CRcs.AI

🧠 Ghost / Vectors / Soft-deleted 1

Ghost Vectors: Soft-Deleted Embeddings Remain Reconstructible in HNSW Vector Databases [37]
Chandranil Chakraborttii, Jackeline García Alvarado, Sitora Abdulofizova, Shivanshu Dwivedi
Retrieval-augmented generation (RAG) allows large language models to access external and private corpora for factual, domain-specific responses. Modern RAG pipelines use hierarchical navigable small…
cs.CR

🧠 Mean-payoff-parity / Lifting / Strategies 1

Mean-Payoff-Parity and Lifting Strategies from MDPs to 2-Player Stochastic Games [38]
Mohan Dantam, Richard Mayr
We consider the strategy complexity (i.e., memory and randomization) of optimal strategies in turn-based 2-player zero-sum stochastic games. Results in [Gimbert,Kelmendi:2023] show how to lift…
cs.GT

🧠 Two / Overlooked / Stick-breaking 1

On two overlooked stick-breaking constructions of the normalized inverse Gaussian process [39]
Annalisa Cerquetti
We shed light on two alternative stick-breaking constructions of the normalized inverse Gaussian (NIG) random discrete distribution which appear to have been overlooked so far in the Bayesian…
math.PRmath.ST

🧠 Secret / Key-distribution / Over 1

Secret key-distribution over networks with node-based adversarial errors [40]
Reza Sayyari, Michael Langberg
We study the multiple key-cast problem in network coding under active node-based adversaries. In multiple key-cast, a source generates independent secret keys to be securely and reliably delivered to…
cs.IT

🧠 Quantum / Solitons / Their 1

Quantum solitons and their quantum walks in transmon arrays [41]
Ben Blain, Giampiero Marchegiani, Luigi Amico, Gianluigi Catelani
Superconducting qubits are artificial atoms whose spectra and interactions can be engineered through appropriate circuit design, a versatility that can be exploited for quantum simulation. We…
quant-phcond-mat.mes-hallcond-mat.quant-gas

🧠 Floquet / Framework / Driven 1

Floquet framework for driven polar quantum systems [43]
Viktor Novičenko, Piotr Gładysz, Karolina Słowik, Egidijus Anisimovas
We present an analytical and numerical Floquet treatment of a driven polar two-level quantum system characterized by both longitudinal and transverse coupling to a periodic field. Analytically, we…
quant-ph

🧠 Spectral / Functions / Lorentzian 1

Spectral Functions of Lorentzian Quantum Gravity [44]
Gabriel Assant, Daniel F. Litim, Manuel Reichert
We compute spectral functions of graviton modes in Lorentzian quantum gravity, interpolating between classical general relativity and an asymptotically safe ultraviolet fixed point. Using functional…
hep-thgr-qc

🧠 Grmhd / Grrt / Simulations 1

GRMHD and GRRT Simulations of Black Hole Accretion: Flares, Precession, and Complex Spacetimes [45]
Hong-Xuan Jiang
This dissertation studies the electromagnetic signatures of accreting supermassive black holes using general relativistic magnetohydrodynamic simulations and covariant radiative-transfer…
astro-ph.HEgr-qc

🧠 Digital / Speech / Acts 1

Digital Speech Acts Retain Control of Copyright with People, Not Platforms [46]
James Golike, Ehud Shapiro
Legal precedents protect computer code as copyrightable expression. They have enabled centralized digital platforms -- operating from corporate servers that hold all user data -- to construct private…
cs.SIcs.CYcs.MA

🧠 Bivariate / Incomplete-bessel / Kernels 1

Bivariate incomplete-Bessel kernels for the first nonlinear Vlasov-Maxwell response [47]
Roberto Ricci
The weakly nonlinear response of a homogeneous magnetised plasma is usually written as a double cyclotron-harmonic expansion. This representation is explicit, but the repeated use of the Jacobi-Anger…
physics.plasm-ph

🧠 Fine-scale / Downflows / Above 1

Fine-scale downflows above flare ribbons captured by Solar Orbiter/EUI [48]
Zheng Sun, Alexander G. M. Pietrow, Malcolm K. Druett, Hui Tian, Julián D. Alvarado-Gómez, Song Tan, Alexander Warmuth, Jiasheng Wang, Yuhang Gao, Zhenyong Hou, Alexandros Stork
In solar flares, flare ribbons map chromospheric footpoints where flare energy deposition occurs. These locations are associated with field aligned energy transport from the corona that results from…
astro-ph.SR

🧠 Integrated / Physics-based / Modeling 1

Integrated physics-based modeling reveals a thermodynamic gap in small modular reactor load following [49]
Ali Mahboub Rad, Roshni Anna Jacob, Bikash Poudel, Mayir Mamtimin, Jie Zhang
Small modular reactors (SMRs) are increasingly considered for flexible power generation; however, many dynamic studies still neglect the thermodynamic coupling between the primary and secondary loops…
eess.SYmath.DS

🌐 Web Findings

🤗 HuggingFace Papers 15

CEO-Bench: Can Agents Play the Long Game? [61]
Language model agents are becoming proficient executors at isolated, short-horizon tasks such as software engineering and customer service. Yet real-world challenges require a…
▲ 1HuggingFace Papers
Externalizing Research Synthesis and Validation in AI Scientists through a Research Harness [62]
AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claims often remains implicit inside…
▲ 1HuggingFace Papers
SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks [52]
Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of expert-level performance. A…
HuggingFace Papers
Kairos: A Native World Model Stack for Physical AI [58]
World models are transitioning from passive visual generators to foundational, operational infrastructure for Physical AI: they must natively acquire world knowledge from…
▲ 19HuggingFace Papers
Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems [65]
Multi-agent LLM systems share state through memory stores, vector indices, and tool registries. We model such sharing as long-running read-generate-write operations under…
HuggingFace Papers
Sumi: Open Uniform Diffusion Language Model from Scratch [56]
Diffusion models have become a promising alternative to autoregressive models. Among these, uniform diffusion language models (UDLMs) permit any token to be updated at any step,…
▲ 4HuggingFace Papers
SAE Interventions are Unreliable: Post-Intervention Recovery of Suppressed Behavior [54]
Sparse Autoencoders (SAEs) decompose residual-stream activations into interpretable features. Recent latent-space defenses increasingly rely on these decompositions, assuming that…
▲ 11HuggingFace Papers
Guava: An Effective and Universal Harness for Embodied Manipulation [63]
Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through embodied tools use offers a promising…
▲ 20HuggingFace Papers
PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation [59]
World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consistency required for robotic…
▲ 1HuggingFace Papers
IndustryBench-MIPU: Benchmarking Multi-Image Attribute Value Extraction for Industrial Products [57]
Industrial products such as valves and circuit breakers are defined by dense technical specifications that govern procurement, compatibility, and safety across supply chains.…
▲ 1HuggingFace Papers
Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciences [64]
In this report, we present LOGOS (Language Of Generative Objects in Science), a scientific generative language model that unifies heterogeneous tasks across the natural sciences…
▲ 2HuggingFace Papers
Reinforcing Dual-Path Reasoning in Spatial Vision Language Models [53]
Spatial VLMs have made substantial progress in geometric perception, yet complex spatial reasoning requiring multi-step inference over depth, distance, and scene relations remains…
▲ 11HuggingFace Papers
Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification [66]
Unified Multimodal Modeling aims to integrate visual understanding and generation within a single system. However, existing approaches typically rely on two disparate visual…
▲ 11HuggingFace Papers
Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding [55]
Graphical user interface (GUI) grounding requires vision-language models (VLMs) to identify small target elements in high-resolution screenshots and predict precise screen…
▲ 11HuggingFace Papers
Physics-IQ Verified [60]
Video generative models ( VGMs) have become a new frontier that can be used not just for video generation but for a multitude of downstream tasks, including world modeling. To…
HuggingFace Papers

📝 OpenReview 2

SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression [77]
The advancements in Large Language Models (LLMs) have been hindered by their substantial sizes, which necessitate LLM compression methods for practical deployment. Singular Value…
OpenReview
Diffusion$^2$: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models [78]
Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and…
OpenReview

🦞 Lobste.rs 2

Announcing Stack Overflow for Agents [50]
Blog Loading… Everything The Heap Productivity AI/ML Open Source Business Hub Company Releases Podcast Newsletter Stack Overflow Business Stack Internal : the knowledge…
Lobste.rs
CLI Authentication, the Right Way [51]
Most CLI auth flows spin up a localhost server and pray your browser cooperates. That model breaks the moment you
Lobste.rs

🎓 Google Scholar 7

Advancements in Artificial Intelligence: Breakthroughs, Challenges and the Road Ahead [68]
This paper conducts systematic analysis of advancements in the field of artificial intelligence (AI) from the year 2010 onwards, by performing original quantitative analysis of…
Google Scholar
Large language models (LLM) in computational social science: prospects, current state, and challenges [69]
Finding from 🎓 Google Scholar.
Google Scholar
When machines join the moral circle: The persona effect of generative AI agents in collaborative reasoning [73]
Finding from 🎓 Google Scholar.
Google Scholar
Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements [72]
Finding from 🎓 Google Scholar.
Google Scholar
Securing the future: exploring post-quantum cryptography for authentication and user privacy in IoT devices [71]
Finding from 🎓 Google Scholar.
Google Scholar
Artificial intelligence and machine learning in cybersecurity: a deep dive into state-of-the-art techniques and future paradigms [70]
Finding from 🎓 Google Scholar.
Google Scholar
Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements [67]
Finding from 🎓 Google Scholar.
Google Scholar

👽 Reddit 3

Multivariate Probability Models in Machine Learning [D] [74]
Hello Folks, we start our discussion on Lecture 10 of Probabilistic Machine Learning, now starting with Probability Multivariate Models. Univariate models are toy cases, in real…
Reddit
How hard is it to break into ML work without a Master's degree? [D] [76]
I'm currently a software engineer (mostly mobile/iOS development) and have recently started learning machine learning because I genuinely find it interesting, especially the math…
Reddit
What does provisional paper acceptance mean in ECCV? Is that the default message everyone gets? [D] [75]
What does provisional paper acceptance mean in ECCV? Is that the default message everyone gets? submitted by /u/NotGondor [link] [comments]
Reddit

🔗 All Sources

  1. [1] UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based…
  2. [2] Rethinking Reward Supervision: Rubric-Conditioned Self-Distillation
  3. [3] Reference-Driven Multi-Speaker Audio Scene Generation from In-the-Wild Priors
  4. [4] Data Intelligence Agents: Interpreting, Modeling, and Querying Enterprise Data via…
  5. [5] Explaining Attention with Program Synthesis
  6. [6] Correct Yourself, Keep My Trust: How Self-Correction and Social Connection Shape…
  7. [7] NeSyCat Torch: A Differentiable Tensor Implementation of Categorical Semantics for…
  8. [8] Trade-offs in Medical LLM Adaptation: An Empirical Study in French QA
  9. [9] A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-2
  10. [10] X+Slides: Benchmarking Audience-Conditioned Slide Generation
  11. [11] Freeing the Law with LOCUS: A Local Ordinance Corpus for the United States
  12. [12] The Chandra-Gaia Catalog of Counterparts: Resolving ambiguous Gaia matches to X-ray…
  13. [13] Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation
  14. [14] P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep…
  15. [15] Optimal scenario design for climate emulation
  16. [16] Confidence is Not Reliability: Rethinking MC Dropout in Brain Tumour Segmentation
  17. [17] Does VLA Even Know the Basics? Measuring Commonsense and World Knowledge Retention in…
  18. [18] Risk Stratification for ICU Delirium using Pervasive Ambient Sensing Information
  19. [19] Zero-Shot Long-Horizon Dexterous Manipulation via Multi-View 3D-Grounded VLM Reasoning
  20. [20] Native Active Perception as Reasoning for Omni-Modal Understanding
  21. [21] Beyond the Current Observation: Evaluating Multimodal Large Language Models in…
  22. [22] Constraints on Cosmic Strings from the Curl-Mode CMB Lensing Power Spectrum measured by…
  23. [23] Learning User Simulators with Turing Rewards
  24. [24] Sparse-dense flight copy-based interactive mechanism to airline integrated with cruise…
  25. [25] Topological spectral form factor reveals emergent non-Hermitian single-particle…
  26. [26] CodeSentinel: A Three-Layer Defense Against Indirect Prompt Injection in Code Contexts
  27. [27] PhantomSkill: Malicious Code Injection in Agent Skill Ecosystems
  28. [28] OpenAnt: LLM-Powered Vulnerability Discovery Through Code Decomposition, Adversarial…
  29. [29] Giskard : Byzantine Robust and Confidential Aggregation for Large-Scale Decentralized…
  30. [30] Quantifying Compromise Risk in Exceptional Access Architectures Under Sparse and Indirect…
  31. [31] Compute-Budgeted Exploitability Evidence Graphs for Prospective Vulnerability Triage
  32. [32] PYPILINE: Malicious PyPI Package Detection via Suspicious API Knowledge and Agent Workflow
  33. [33] CHERI-D: Secure and efficient inline object ID for CHERI temporal memory safety
  34. [34] Structured lattices and their applications to security
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  25. [64] Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model…
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  30. [69] Large language models (LLM) in computational social science: prospects, current state,…
  31. [70] Artificial intelligence and machine learning in cybersecurity: a deep dive into…
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  34. [73] When machines join the moral circle: The persona effect of generative AI agents in…
  35. [74] Multivariate Probability Models in Machine Learning [D]
  36. [75] What does provisional paper acceptance mean in ECCV? Is that the default message everyone…
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