Carlos's Debrief

June 15, 2026 04:00
43ArXiv Papers
44Web Findings
87Total 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 15, 2026 04:00 — Curated by Hermes Research Scout

⚡ Quick Summary

📰 News Headlines

🗡️ Relevant to your Katana work 1

📄 ArXiv Papers

🧠 Reasoning / Clinhallu / Benchmark 2

ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning [1]
Sicheng Yang, Hangjie Yuan, Wenjun Zhang, Jinwang Wang, Yichen Qian, Weihua Chen, Fan Wang, Lei Zhu
Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision support. Existing medical hallucination benchmarks mainly focus on data collection,…
cs.CVcs.AIcs.CL
CORA: Analyzing and bridging thinking-answer gap in Multimodal RLVR via Consistency-Oriented Reasoning Alignment [43]
Jiayue Cao, Zhicong Lu, Xuehan Sun, Wei Jia, Hongling Zheng, Changyuan Tian, Zichuan Lin, Wenqian Lv, Nayu Liu
Reinforcement learning with verifiable rewards (RLVR) has successfully elicited the reasoning capabilities of large language models, motivating its extension to multimodal scenarios. Existing methods…
cs.CL

🧠 Gaze / Heads / How 2

Gaze Heads: How VLMs Look at What They Describe [11]
Rohit Gandikota, David Bau
How a vision-language model internally solves the task of describing an image is far from obvious. We find that the model develops a specific mechanism for this: a small set of attention heads in its…
cs.CVcs.CLcs.LG
RATS! Patches Talk Through Registers: Emergent Parts in Register Attention Transformers [21]
Timing Yang, Predrag Neskovic, Jansen Seheult, Wenchao Han, Anand Bhattad, Alan Yuille, Feng Wang
When humans see a bird, they recognize far more than just "bird" -- they see a head, wings, and talons, a structured assembly of reusable parts that can be identified across every bird they have ever…
cs.CV

🧠 Coordinated / Preference / Multi-objective 1

Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning [2]
Pengxin Wang, Lihao Guo, Yi Xie, Bo Liu, Siyang Cao, Jingdi Chen
Cooperative multi-objective multi-agent reinforcement learning (MOMARL) models team decision making under multiple, potentially conflicting objectives. In this setting, conflicts arise not only…
cs.MAcs.AI

🧠 Flood / Harvest / Provable 1

Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit [3]
Xiaoyu Li, Andi Han, Dai Shi, Zheng Gao, Jiaojiao Jiang, Junbin Gao
AI systems coupled to proof assistants now generate formal mathematics at scale, and the gap between what a checker can verify and what a mathematician would value has become the binding constraint.…
cs.LGcs.AIcs.CL

🧠 Cottonleafvision / Explainable / Robust 1

CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification [4]
Rafi Ahamed, Md. Abir Rahman, Tasnia Tarannum Roza, Munaia Jannat Easha, Md. Asif Khan, Sudeepta Mandal
Globally, cotton is a highly economically beneficial crop, as the textile industry heavily depends on it. So, the precise identification and detection of cotton leaf disease is crucial for economic…
cs.CVcs.AI

🧠 Towards / Direct / Latent-space 1

Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows [5]
Shikun Liu, Mufei Li, Dongqi Fu, Haoyu Wang, Yinglong Xia, Hong Li, Hong Yan, Pan Li
Large language models increasingly serve as execution engines for agentic systems, yet they still consume context through a sequential text interface. This creates a mismatch with modern structured…
cs.AIcs.CL

🧠 Giving / Headache / Acoustic 1

Giving AI a Headache: Acoustic Adversarial Attacks to Computer Vision Applications [6]
Nicole Villavicencio-Garduño, Maksim Ekin Eren, Milo Prisbrey, Ben Migliori, Michael Teti
Artificial Intelligence (AI) is increasingly used to automate a variety of real-world computer vision (CV) applications, such as autonomous vehicle control, facial recognition, and security cameras.…
cs.CVcs.AI

🧠 Abstracting / Cross-domain / Action 1

Abstracting Cross-Domain Action Sequences into Interpretable Workflows [7]
Gaurav Verma, Scott Counts
Sequential or time-stamped interaction logs provide objective records of digital application usage, yet their granularity and noise often obscure meaningful insights into people's work. Such insights…
cs.AIcs.CLcs.LG

🧠 Listening / Attention / Entropy-guided 1

Listening with Attention: Entropy-Guided Explainability for Transformer-Based Audio Models [8]
Ravi Ranjan, Utkarsh Grover, Xiaomin Lin, Agoritsa Polyzou
Transformer-based automatic speech recognition (ASR) models such as Whisper are highly accurate, but their predictions remain difficult to interpret. Existing explainable AI (XAI) methods often lack…
cs.SDcs.AI

🧠 Self-supervised / Speech / Mixture-of-experts 1

From Self-Supervised Speech Models to Mixture-of-Experts for Robust Anti-Spoofing [9]
Hugo Daumain, Driss Matrouf, Khaled Khelif, Mickael Rouvier
Recent advances in speech generation have significantly improved the naturalness of synthetic speech, making spoofing detection increasingly challenging. A key limitation of current anti-spoofing…
cs.SDcs.AI

🧠 When / Good / Verifiers 1

When Good Verifiers Go Bad: Self-Improving VLMs Can Regress on New Tasks [10]
Jianzhe Lin
Verifier-driven self-DPO is a common recipe for self-improving production visual-language models. In this setup, a frozen verifier scores candidate generations, the top- and bottom-scoring candidates…
cs.CRcs.AI

🧠 Persona-pruner / Sculpting / Lightweight 1

Persona-Pruner: Sculpting Lightweight Models for Role-Playing [12]
Jinsu Kim, Jihoon Tack, Noah Lee, Jongheon Jeong
Language Models (LMs) have shown remarkable potential as role-playing chatbots, delivering consistent, stylized interactions when given a specification of a character or user persona. However,…
cs.LGcs.CL

🧠 Complexity / Measure / Active 1

A Complexity Measure for Active Learning in Multi-group Mean Estimation [13]
Abdellah Aznag, Rachel Cummings, Adam N. Elmachtoub
We study a \emph{max-risk} objective for active learning in a multi-group mean estimation $d$-armed bandits: a learner adaptively allocates a budget of $T$ samples across $d$ groups to minimize the…
cs.LGcs.IT

🧠 Hump-kd / Hybrid / Uncertainty-aware 1

HumP-KD: A Hybrid Uncertainty-Aware Multi-Stage Progressive Knowledge Distillation Framework for Efficient Fire Classification [14]
Mohammed Arif Mainuddin, Najifa Tabassum, Omar Ibne Shahid, Riasat Khan
Real-time fire classification systems require models that are simultaneously accurate, computationally efficient, and deployable on resource-constrained hardware. This work proposes \textbf{HumP-KD},…
cs.CVcs.LG

🧠 Optimal / Hidden-target / Online 1

Optimal Hidden-Target Learning for Online Inventory Optimization on General Convex Sets [15]
Anthony Pineci, Yunzong Xu
Online inventory optimization (OIO) is online convex optimization with physical memory: inventory carryover makes the feasible action set depend on the past. A natural principle, used in stochastic…
cs.LGeess.SYmath.OC

🧠 Computation / Compressed / Probably 1

Compressed Computation is (probably) not Computation in Superposition [16]
Jai Bhagat, Sara Molas-Medina, Giorgi Giglemiani, Stefan Heimersheim
We study whether the Compressed Computation (CC) toy model (Braun et al., 2025) is an instance of computation in superposition. The CC model appears to compute 100 ReLU functions with just 50…
cs.LG

🧠 When / Write / Suppress 1

When to Write and When to Suppress: Route-Specialized Dual Adapters for Memory-Assisted Knowledge Editing [17]
Yining Huang
Knowledge editing systems must update selected facts while preserving nearby but irrelevant behavior. This paper studies this problem in a memory-assisted setting where an edit memory is retrieved at…
cs.LG

🧠 Beyond / Task / Performance 1

Beyond task performance: Decoding bioacoustic embeddings with speech features [18]
Ines Nolasco, Jules Cauzinille, Marius Miron, Gagan Narula, Milad Alizadeh, Emmanuel Fernandez, Matthieu Geist, Ellen Gilsenan-McMahon, Olivier Pietquin, Emmanuel Chemla, Sara Keen
Pretrained audio embeddings are standard in bioacoustics, yet little is known about which acoustic features these models encode, nor which are useful for a given task. This hinders transparency and…
cs.LGcs.SD

🧠 Edges / Planetary / Systems 1

The Edges of Planetary Systems: Falling Off the Kuiper Cliff in a Dissipating Gas Disk [19]
Rixin Li, Eugene Chiang
Probably the last planetesimals to have formed from dust in the solar nebula are Cold Classical Kuiper belt objects (CCKBOs). To the extent that they are isolated and unchanged since birth, CCKBOs…
astro-ph.EP

🧠 Omnivideo-100k / Dataset / Audio-visual 1

OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains [20]
Xinyue Cai, Chaoyou Fu, Yi-Fan Zhang, Ran He, Caifeng Shan
Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short clips and generate…
cs.CV

🧠 Repfusion / Leveraging / Multimodal 1

RepFusion: Leveraging Multimodal Priors for Denoising in Representation Space [22]
Xichen Pan, Aashu Singh, Satya Narayan Shukla, Xiangjun Fan, Shlok Kumar Mishra, Saining Xie
Large language models (LLMs) are widely used in text-to-image (T2I) systems, but they are typically limited to text encoding, while denoising is handled by newly trained generative backbones. The…
cs.CV

🧠 Instruct-particulate / Scaling / Feed-forward 1

Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control [23]
Ruining Li, Yuxin Yao, Matt Zhou, Chuanxia Zheng, Christian Rupprecht, Joan Lasenby, Shangzhe Wu, Andrea Vedaldi
Reconstructing articulated 3D objects is important for animation, gaming, and robotic simulations. Recent neural networks can estimate the articulated structure of 3D objects, but their…
cs.CVcs.GRcs.RO

🧠 Security / Threats / Their 1

Security Threats and Their Impact on Blockchain Interoperability: Identification and Countermeasures [24]
Shawn M. Reynolds, Hassan Reza
Blockchain interoperability enables independent blockchain systems to communicate and exchange assets across heterogeneous networks. However, the lack of comprehensive security mechanisms remains a…
cs.SEcs.CR

🧠 Detecting / Bot / Detection 1

Detecting Bot Detection: Prevalence, Techniques, and Implications for Web Measurement Research [25]
Ralf Gundelach, Michael Mühlhauser, Dominik Herrmann
Browser automation frameworks are essential tools for security and privacy research on the web, yet bot detection scripts increasingly probe their artifacts, threatening measurement validity as…
cs.CRcs.CY

🧠 Shield / Target / Denial-of-service 1

From Shield to Target: Denial-of-Service Attacks on LLM-Based Agent Guardrails [26]
Yuguang Zhou, Xunguang Wang, Pingchuan Ma, Zhantong Xue, Zhaoyu Wang, Shuai Wang
LLM-based guardrails have emerged as a highly effective defense against prompt injection and jailbreak attacks in autonomous agents. However, we reveal that the very reasoning and task-following…
cs.CRcs.AI

🧠 Securing / Future / Iomt 1

Securing the Future of IoMT in the Post-Quantum Era: An Edge-Native Federated Learning Approach [27]
Taym Alshoghri, Deemah H. Tashman, Mohammad Reza Gerami, Soumaya Cherkaoui
Internet of Medical Things (IoMT) devices operate under strict resource constraints while handling highly sensitive health data, making security and privacy critical concerns. Federated learning (FL)…
cs.CRcs.AI

🧠 Breaking / Tinyml / Why 1

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis [28]
Jacob Huckelberry, Andrea Mattia Garavagno, Yuke Zhang, Peter A. Beerel, James Mickens, Vijay Janapa Reddi
Most TinyML hardware accelerators focus on supporting Quantized Neural Networks (QNNs) to meet stringent constraints on power consumption and size. Despite this, the security aspects of quantization…
cs.CR

🧠 Repose / Quantifying / Price 1

REPOSE: Quantifying the Price of Security in Weakly-Hard Real-Time Cyber-Physical Systems [29]
Vijay Banerjee, Monowar Hasan
In contemporary IoT edge devices with real-time requirements, security is primarily enforced through design-time parameters associated with security tasks, leading to mechanisms that operate in an…
cs.CR

🧠 Agentcyberrange / Benchmarking / Frontier 1

AgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Ranges [30]
Fengyu Liu, Jiarun Dai, Yihe Fan, Wuyuao Mai, Ziao Li, Bofei Chen, Jie Zhang, Zheng Lou, Bocheng Xiang, Qiyi Zhang, Xudong Pan, Geng Hong, Yuan Zhang, Min Yang
Frontier AI systems are increasingly capable of cybersecurity tasks, including codebase inspection, vulnerability detection, and exploitation. However, evaluating their offensive capabilities remains…
cs.CRcs.AIcs.LG

🧠 Pseudonym / Scheme / Hybrid 1

Pseudonym Scheme Based on Hybrid Certificates for Security Credential Management System in Vehicular Communications [31]
Abel C. H. Chen, F. J. Hwang, Yu-Chih Wei, Chin-Chen Chang, Bon-Yeh Lin
In recent years, the Institute of Electrical and Electronics Engineers (IEEE) and the European Telecommunications Standards Institute (ETSI) have developed a series of security communication…
cs.CRcs.NIcs.PF

🧠 Stream / Multi-tier / Llm 1

STREAM: Multi-Tier LLM Inference Middleware with Dual-Channel HPC Token Streaming [32]
Anas Nassar, Steve Mohr, Leonard Apanasevich, Himanshu Sharma
Researchers and practitioners working with large language models face a fragmented landscape: local models are free and private but hardware limits the model size and context windows a researcher can…
cs.DCcs.AI

🧠 Chosen-plaintext / Attacks / Double 1

Chosen-Plaintext Attacks of Double Random Phase Encryption with Nonlinear Optical Media [33]
Yan Cheng, Yiwei Chen, Kui Ren, Nathan Soedjak
This paper studies an inverse problem in nonlinear optical encryption. We examine chosen-plaintext attacks (CPA) on a nonlinear optical encryption strategy that integrates double random phase…
physics.opticsmath.NAphysics.comp-ph

🧠 Resolving / Edge / Quantum 1

Resolving the Edge of a Quantum Pyramid [34]
Alvan Arulandu
Standing on the shoulders of giants, we resolve the quantum pyramids conjecture, confirming the globally information-optimal measurement for an ensemble of equiangular equiprobable pure states, as…
quant-phmath-phmath.FA

🧠 Scalar / Dissipation / Anomaly 1

Scalar dissipation anomaly and scalar-gradient scaling in turbulence: A joint velocity-scalar multifractal view [35]
Dhawal Buaria
We revisit the problem of scalar dissipation anomaly and scaling of scalar gradients in passive scalar turbulence using theory and data from well-resolved direct numerical simulations (DNS) on grid…
physics.flu-dyncond-mat.softphysics.comp-ph

🧠 Adasr / Adaptive / Streaming 1

AdaSR: Adaptive Streaming Reasoning with Hierarchical Relative Policy Optimization [36]
Junlong Tong, Wenqi Xu, Yingqi Fan, Anhao Zhao, Xuan Lu, Yang Tan, Xiaoyu Shen
Large reasoning models typically follow a read-then-think paradigm: they observe the complete input, reason over a static context, and then produce the answer. Yet many real-world scenarios are…
cs.CL

🧠 Lehner / Operator / Norm 1

Lehner's operator norm formulas, semidefinite programming, and spiked matrix models [37]
Dmitriy Kunisky
Lehner (1999) derived elegant formulas for the operator norm $\|\mathfrak{X}\|$ of operators of the form $\mathfrak{X} = \mathbf{A}_0 \otimes \mathfrak{1} + \sum_{i = 1}^n \mathbf{A}_i \otimes…
math.PRmath.OAmath.OC

🧠 Monolithic / Hybrid / Quantum 1

Monolithic hybrid quantum dot devices in superconducting twisted bilayer graphene [38]
Alexandra Mestre-Torà, Marta Perego, Clara Galante Agero, Takashi Taniguchi, Kenji Watanabe, Thomas Ihn, Klaus Ensslin, Artem O. Denisov
Gate-tunable superconductivity in magic-angle twisted bilayer graphene (MATBG) has enabled the realization of superconducting devices, such as Josephson junctions, within a single crystal. This…
cond-mat.mes-hall

🧠 Quantum / Geometrical / Description 1

Quantum geometrical description of hole spin qubits far away from the $Γ$-point [39]
Zoltán György, Dmitry Miserev, Jelena Klinovaja, Daniel Loss
Hole spin qubits provide one of the leading platforms for spin-based quantum computing due to their large intrinsic spin-orbit interaction (SOI), which enables fast electrical manipulation. The SOI…
cond-mat.mes-hallquant-ph

🧠 Quasilinear / Equivalence / Checking 1

Quasilinear Equivalence Checking for Detector Error Models [40]
Mathys Rennela
A Detector Error Model (DEM) is a structured representation of error mechanisms in quantum circuits, which has gained popularity in quantum compilation pipelines for its ability to capture…
quant-phcs.LOcs.PL

🧠 Whole-body / Impedance / Predictive 1

Whole-Body Impedance Model Predictive Control for Safe Physical Human--Robot Interaction on Floating-Base Platforms [41]
Yongyan Cao
Floating-base robots must balance under rigid contact constraints while interacting safely with humans. Existing whole-body control~(WBC) frameworks allocate the full joint space to locomotion or…
cs.ROeess.SY

🧠 Private / Information / Retrieval 1

Private Information Retrieval for Large-Scale DNA-Based Data Storage [42]
Gökberk Erdoğan, Daniella Bar-Lev, Rawad Bitar, Antonia Wachter-Zeh, Zohar Yakhini
We investigate Private Information Retrieval (PIR) in the context of synthetic DNA-based data storage. While PIR is a well-studied primitive for digital databases, extending it to DNA-based databases…
cs.IR

🌐 Web Findings

🤗 HuggingFace Papers 27

From AGI to ASI [67]
Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI…
▲ 19HuggingFace Papers
Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents [63]
Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a static retrieve-then-reason…
▲ 46HuggingFace Papers
CARVE: Certified Affordable Repair of Vetoed Maneuvers via Envelopes for Interactive Driving [49]
Interactive driving exposes a failure mode that is easy to miss in rule-aware autonomous-driving stacks: a hard-rule margin can be negative for an ego candidate even though a…
HuggingFace Papers
Measuring Epistemic Resilience of LLMs Under Misleading Medical Context [47]
Large language models (LLMs) now reach expert-level scores on medical licensing exams, encouraging the assumption that high scores imply safe medical judgment while patients…
▲ 11HuggingFace Papers
Benchmarking AI Agents for Addressing Scientific Challenges Across Scales [51]
AI agents are increasingly being developed to accelerate scientific discovery, yet their practical capabilities in real research settings remain poorly understood. Existing…
HuggingFace Papers
When is Your LLM Steerable? [69]
Activation steering offers a lightweight approach to control language models' behavior at inference time, but whether it succeeds or fails heavily depends on the prompt, concept,…
▲ 3HuggingFace Papers
LLM Agents Can See Code Repositories [57]
Coding agents powered by large language models have demonstrated strong performance on software engineering tasks. Yet most agents consume repositories almost entirely as text,…
▲ 10HuggingFace Papers
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI [68]
Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reasoning, action, memory, and…
▲ 22HuggingFace Papers
Skip a Layer or Loop It? Learning Program-of-Layers in LLMs [65]
Large language models (LLMs) perform inference by following a fixed depth and order, non-recurrent execution of all layers. We reveal the wide existence of training-free,…
▲ 9HuggingFace Papers
RedAct: Redacting Agent Capability Traces for Procedural Skill Protection [54]
Users rely on execution traces to observe agent behavior, diagnose failures, and ensure accountability. These traces contain rich procedural detail, including tool invocations,…
▲ 15HuggingFace Papers
APPO: Agentic Procedural Policy Optimization [52]
Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents. However, most existing…
▲ 57HuggingFace Papers
P3D-Bench: Benchmarking MLLMs for Parametric 3D Generation and Structural Reasoning [46]
Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3D generation powered by…
▲ 1HuggingFace Papers
HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry [61]
AI agent performance depends critically on the runtime harness, comprising the prompts, tools, memory, and control flow that mediate how a model observes, reasons, and acts. Yet…
▲ 29HuggingFace Papers
Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack [60]
In this report, we present Hy-Embodied-0.5-VLA, abbreviated as HyVLA-0.5, an end-to-end system that spans the full robot learning stack: data collection, model design, continued…
▲ 6HuggingFace Papers
Orchestra-o1: Omnimodal Agent Orchestration [58]
The recent success of agent swarms has shifted the paradigm of large language model (LLM)-based agents from single-agent workflows to multi-agent systems, highlighting the…
▲ 34HuggingFace Papers
Dense Supervision, Sparse Updates: On the Sparsity and Geometry of On-Policy Distillation [66]
On-policy distillation (OPD) has recently become a prominent post-training recipe as it combines two desirable ingredients: on-policy student trajectories and dense teacher…
▲ 2HuggingFace Papers
Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO [50]
We identify a new dimension for enhancing rollout diversity in Group Relative Policy Optimization (GRPO) for LLMs. While GRPO relies on diverse rollouts, prevailing strategies…
▲ 16HuggingFace Papers
VISTA: View-Consistent Self-Verified Training for GUI Grounding [70]
When applying Group Relative Policy Optimization (GRPO) for GUI Grounding, rollouts are sampled from a single screenshot view; groups often become either all failures on difficult…
▲ 5HuggingFace Papers
Where, What, Why, and Importance: Structured Defect Grounding for Text-to-Image Feedback [71]
Despite generating increasingly photorealistic images, text-to-image (T2I) models still exhibit localized, subtle, and structurally complex failures. Diagnosing these failures…
▲ 15HuggingFace Papers
μ_0: A Scalable 3D Interaction-Trace World Model [62]
World models that capture how actions induce physical change enable scalable robot learning without reliance on embodiment-specific action labels. Pixel-space video models provide…
▲ 1HuggingFace Papers
MBench: A Comprehensive Benchmark on Memory Capability for Video World Models [55]
Recent advancements in video-based world models have demonstrated an unprecedented ability to synthesize high-fidelity visual sequences. However, a fundamental gap persists…
▲ 6HuggingFace Papers
The Hidden Power of Scaling Factor in LoRA Optimization [64]
In Low-Rank Adaptation (LoRA), the scaling factor α is often treated as a mere complement to the learning rate, yet its role in optimization remains poorly understood. In this…
▲ 5HuggingFace Papers
Rethinking RAG in Long Videos: What to Retrieve and How to Use It? [48]
Retrieval-augmented generation is moving beyond text into long, egocentric video, where systems must select query-relevant chunks across multiple modalities and temporal…
▲ 30HuggingFace Papers
Avatar V: Scaling Video-Reference Avatar Video Generation [59]
Generating avatar videos that are not merely visually similar to a target individual but behaviorally recognizable, faithfully reproducing their talking rhythm, gestural…
▲ 4HuggingFace Papers
RhymeFlow: Training-Free Acceleration for Video Generation with Asynchronous Denoising Flow Scheduling [53]
Video generation models based on Diffusion Transformers (DiTs) have achieved remarkable performance in video synthesis, yet they suffer from high inference latency and…
▲ 5HuggingFace Papers
WaveDiT: Distribution-Aware Wavelet Flow Matching for Efficient 3D Brain MRI Synthesis [45]
Large and demographically balanced datasets are essential for reliable neuroimaging biomarkers. Full-resolution 3D brain MRI synthesis can support data augmentation in this…
HuggingFace Papers
OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired Data [56]
Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and precise control. Existing methods either directly use…
▲ 76HuggingFace Papers

📝 OpenReview 2

SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression [86]
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 [87]
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 1

curl summer of bliss [44]
The curl project will not accept or otherwise handle any vulnerability reports during the month of July 2026. We call it the curl summer of bliss. curl's submission form on…
Lobste.rs

🎓 Google Scholar 6

Large language models (LLM) in computational social science: prospects, current state, and challenges [74]
Finding from 🎓 Google Scholar.
Google Scholar
Securing the future: exploring post-quantum cryptography for authentication and user privacy in IoT devices [76]
Cluster Computing - With the emergence of quantum computers, traditional cryptographic methods are vulnerable to attacks, emphasizing the need for post-quantum cryptography to…
Google Scholar
Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements [77]
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 [75]
Finding from 🎓 Google Scholar.
Google Scholar
Early identification of breakthrough technologies: Insights from science-driven innovations [72]
Finding from 🎓 Google Scholar.
Google Scholar
Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements [73]
Finding from 🎓 Google Scholar.
Google Scholar

📰 Hacker News 2

'It's a hurricane warning': Guardrails around powerful AI models may be too late [78]
Finding from 📰 Hacker News.
Hacker News
Quantum Horizon: Quantum Computing as a Threat to Bitcoin and Ethereum [79]
Finding from 📰 Hacker News.
Hacker News

👽 Reddit 6

PhD study: UX Designers & AI/ML Practitioners to test a "Trust in LLM-based Chatbots" Design Method (~25 min, anonymous) [R] [82]
Hi everyone, I'm a PhD researcher at Mainz University of Applied Sciences, Germany. My dissertation looks at how interface and UX design shape user trust in AI/LLM-based chatbots…
Reddit
How does the ML community view evolutionary algorithm research? Career implications of an EA PhD? [D] [80]
How does the ML research community feel about evolutionary algorithms? Should I do a PhD in this area? Quick remark: I know some people in the ML community dunk on evolutionary…
Reddit
Why do frontier AI labs send so many people to conferences? [D] [83]
Recent years I see plenty of folks from OpenAI and Anthropic attending conferences like ICML/Neurips, yet obviously few are presenting. Are they mainly recruiting? Following…
Reddit
Worth going to ICML during ACL? [D] [84]
I have a main paper in ACL and a workshop paper in ICML. I'm looking for jobs in U.S. as a graduating student. Would it be worth going to ICML after ACL presentation such that I…
Reddit
Quant firms at ICML 2026 [D] [81]
I noted that in ICML 2026, quant firms are flocking and sponsoring as Diamond sponsors. Any reason? Source: https://icml.cc/sponsors/sponsors-list?year=2026at submitted by…
Reddit
I’d Like to Try for a Google PhD Internship [R] [85]
I’d like to apply for a Google PhD internship, but I currently have only one publication and three ongoing projects that will hopefully be published someday. Do I still have a…
Reddit

🔗 All Sources

  1. [1] ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning
  2. [2] Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning
  3. [3] Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics…
  4. [4] CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf…
  5. [5] Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows
  6. [6] Giving AI a Headache: Acoustic Adversarial Attacks to Computer Vision Applications
  7. [7] Abstracting Cross-Domain Action Sequences into Interpretable Workflows
  8. [8] Listening with Attention: Entropy-Guided Explainability for Transformer-Based Audio Models
  9. [9] From Self-Supervised Speech Models to Mixture-of-Experts for Robust Anti-Spoofing
  10. [10] When Good Verifiers Go Bad: Self-Improving VLMs Can Regress on New Tasks
  11. [11] Gaze Heads: How VLMs Look at What They Describe
  12. [12] Persona-Pruner: Sculpting Lightweight Models for Role-Playing
  13. [13] A Complexity Measure for Active Learning in Multi-group Mean Estimation
  14. [14] HumP-KD: A Hybrid Uncertainty-Aware Multi-Stage Progressive Knowledge Distillation…
  15. [15] Optimal Hidden-Target Learning for Online Inventory Optimization on General Convex Sets
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