Carlos's Debrief

June 1, 2026 04:00
0ArXiv Papers
45Web Findings
45Total 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 1, 2026 04:00 — Curated by Hermes Research Scout

⚡ Quick Summary

📰 News Headlines

📄 ArXiv Papers

🧠 LLMs 0

No new papers this cycle.

🎨 Machine Learning 0

No new papers this cycle.

🔐 Security & Crypto 0

No new papers this cycle.

🕵️ Zero Knowledge 0

No new papers this cycle.

⚛️ Quantum 0

No new papers this cycle.

🛡️ AI Safety 0

No new papers this cycle.

🤖 Agents 0

No new papers this cycle.

🌐 Web Findings

🦞 Lobste.rs 3

It's Not Just X. It's Y [1]
Lobste.rs • ai • 2026-05-31
Against the Quantification of Integrity When the measure of language becomes its target, it ceases to be good language. 💡Nerd Rating: 1/5. I discuss the origins of certain linguistic tics in LLMs and what it means for writing …
Lobste.rsai2026-05-31
On Reading SRAMs in IR Images, and Establishing Bounds on Trust [2]
Lobste.rs • security • 2026-05-31
Last month’s name that ware demonstrates that even though non-destructive IR imaging is not capable of resolving an individual bit cell, at least at 22nm it is still possible to constrain the number of bits in an SRAM macro …
Lobste.rssecurity2026-05-31
ChatGPT Won't Let You Type Until Cloudflare Reads Your React State. I Decrypted the Program That Does It [3]
Lobste.rs • privacy • 2026-03-30
This reverse-engineering post argues that ChatGPT's web client gates text entry behind Cloudflare code that inspects client-side React state before input is enabled …
Lobste.rsprivacy2026-03-30

🎓 Google Scholar 5

Early identification of breakthrough technologies: Insights from science-driven innovations [4]
Google Scholar • machine learning breakthroughs
This item reviews early identification of breakthrough technologies: insights from science-driven innovations and its broader implications for machine learning progress …
Google Scholarmachine learning breakthroughs
Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements [5]
Google Scholar • machine learning breakthroughs
This review surveys how machine learning is being used to accelerate catalyst discovery and optimization for methane dry reforming. It matters because AI methods are increasingly flowing into energy and climate-relevant materials research …
Google Scholarmachine learning breakthroughs
Artificial intelligence and machine learning in cybersecurity: a deep dive into state-of-the-art techniques and future paradigms [6]
Google Scholar • AI security cybersecurity
This review synthesizes current uses of AI and machine learning across cybersecurity, including adversarial AI, automated threat intelligence, and AI-driven security orchestration …
Google ScholarAI security cybersecurity
Securing the future: exploring post-quantum cryptography for authentication and user privacy in IoT devices [7]
Google Scholar • cryptography post-quantum
This paper reviews post-quantum approaches for authentication and privacy in long-lived IoT systems that may still be deployed when quantum attacks become practical. It matters because connected devices are slow to replace …
Google Scholarcryptography post-quantum
Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements [8]
Google Scholar • quantum computing algorithms
This review surveys hybrid and native quantum machine-learning approaches across optimization, science, and secure communications while separating mature ideas from speculative ones …
Google Scholarquantum computing algorithms

🧑‍💻 Hacker News 0

No new findings this cycle.

🤗 HuggingFace 37

SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? [9]
Sy-Tuyen Ho, Minghui Liu, Huy Nghiem, Furong Huang
Autonomous AI research agents aim to accelerate scientific discovery by automating the research pipeline, from hypothesis generation to peer review. However …
HuggingFacedaily curated papers2026-05-28
Emergent Languages in Populations of Language Model Agents: From Token Efficiency to Oversight Evasion [10]
Stine Lyngsø Beltoft, William Brach, Federico Torrielli, Jacob Nielsen, Annemette Brok Pirchert
Monitoring autonomous language model agents currently relies mostly on surface behavior. But what happens when agent populations invent new languages with the goal of avoiding human oversight. …
HuggingFacedaily curated papers2026-05-29
PEEK: Picking Essential frames via Efficient Knowledge distillation [11]
Killian Steunou, Anas Filali Razzouki, Khalil Guetari, Mounîm A. El-Yacoubi, Yannis Tevissen
Video-language models can process only a limited number of frames, making frame selection a key bottleneck for efficient video captioning. Most captioning pipelines still rely on uniform sampling …
HuggingFacedaily curated papers2026-05-29
iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning [12]
Chang-Bin Zhang, Yujie Zhong, Qiang Zhang, Kai Han
While visually grounded Chain-of-Thought (CoT) has emerged as a promising paradigm to enhance fine-grained perception in multimodal large language models (MLLMs), its efficacy during the inference phase remains underexplored …
HuggingFacedaily curated papers2026-05-29
Benchmarking Composed Image Retrieval for Applied Earth Observation [13]
Bill Psomas, Dionysis Christopoulos, Thanasis Petropoulos, Nikos Efthymiadis, Ioannis Kakogeorgiou
Remote sensing composed image retrieval (RSCIR) enables search in large satellite image archives using composed queries that combine a reference image with a textual modifier …
HuggingFacedaily curated papers2026-05-23
DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization [14]
Jian Mu, Tianyi Lin, Chengwei Qin, Zhongxiang Dai, Yao Shu
Large language models are increasingly deployed in multi-turn interactive settings where users or environments can iteratively provide lightweight feedback. Unfortunately …
HuggingFacedaily curated papers2026-05-29
Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents [15]
Tianpeng Bu, Xin Liu, Qihua Chen, Hao Jiang, Shurui Li
While GUI agents have advanced rapidly, they often lack the robustness to recover from their own errors, hindering real-world deployment. To bridge this gap at both the evaluation and data levels …
HuggingFacedaily curated papers2026-05-28
Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)? [16]
Yue Zhang, Zun Wang, Han Lin, Yonatan Bitton, Idan Szpektor
Spatial reasoning is a fundamental capability for vision-language models (VLMs) deployed in real-world environments. However, visual observations are inherently limited representations of a 3D world: occlusion can render objects invisible, …
HuggingFacedaily curated papers2026-05-28
SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks [17]
Wai-Chung Kwan, Aryo Pradipta Gema, Joshua Ong Jun Leang, Pasquale Minervini
Self-play can train language models without external supervision. However, existing methods require rule-checkable answers, leaving open-ended tasks dependent on curated prompts or frontier-model judges. …
HuggingFacedaily curated papers2026-05-29
The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement [18]
Xiaobo Wang, Tong Wu, Min Tang, Jiaqi Li, Qi Liu
Building strong reward models (RMs) for language model alignment is bottlenecked by the cost and difficulty of acquiring diverse and reliable preference data from human annotation or judge models …
HuggingFacedaily curated papers2026-05-29
Count Anything [19]
Mengqi Lei, Shuokun Cheng, Wei Bao, Shaoyi Du, Jun-Hai Yong
Object counting remains fragmented across domain-specific datasets and task formulations, despite rapid progress in generalist vision models. Existing counting models are often tailored to scenarios such as crowds, vehicles, cells …
HuggingFacedaily curated papers2026-05-29
AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling [20]
Yiheng Li, Zhuo Li, Ruibing Hou, Yingjie Chen, Hong Chang
Conditional human motion generation remains a fundamental challenge in computer vision and robotics. Despite significant progress, current methods are often constrained by fixed modality configurations and task-specific architectures …
HuggingFacedaily curated papers2026-05-28
The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction [21]
Shu Wan, Abhinav Gorantla, Huan Liu, K. Selçuk Candan
Under standard graphical assumptions, the Markov boundary of a target variable is the smallest set of features that renders every other feature redundant. Once the boundary is observed …
HuggingFacedaily curated papers2026-05-28
Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal [22]
Junlin Wang
Learning visuomotor policies via behavior cloning typically involves mimicking expert demonstrations collected by human operators. However, natural human demonstrations inherently contain high-frequency noise, such as intermittent jerks …
HuggingFacedaily curated papers2026-05-27
Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios [23]
Changhao Pan, Rui Yang, Han Wang, Zhuan Zhou, Xuming He
Recent advances in speech generation have enabled high-fidelity synthesis, yet systematic evaluation of models under long-context conditions remains largely underexplored …
HuggingFacedaily curated papers2026-05-27
Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer [24]
Ke Lei, Yu Zhang, Changhao Pan, Xueyi Pu, Wenxiang Guo
Real-time and accurate spatial audio generation is pivotal for delivering an immersive experience. However, existing spatial audio synthesis technologies are often encumbered by a tradeoff between generation quality and high inference late …
HuggingFacedaily curated papers2026-05-29
SwanVoice: Expressive Long-Form Zero-Shot Speech Synthesis for Both Monologue and Dialogue [25]
Ruiqi Li, Yu Zhang, Changhao Pan, Ke Lei, Xiang Yin
Zero-shot text-to-speech (TTS) has improved substantially for single-speaker synthesis, yet expressive long-form multi-speaker dialogue remains difficult …
HuggingFacedaily curated papers2026-05-29
FRAPPE: Full Input, Residual Output Autoencoding with Projection Pursuit Encoder [26]
Dan Jacobellis, Neeraja J. Yadwadkar
Media compression standards have reached a plateau in terms of the rate-distortion-complexity trade-off, limiting the ability to offload expensive AI perception to the cloud in applications like robotics, wearables, and remote sensing …
HuggingFacedaily curated papers2026-05-27
OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents [27]
Jiahao Ying, Boxian Ai, Wei Tang, Siyuan Liu, Yixin Cao
Skills, i.e., structured workflow instructions distilled for large language models (LLMs), are becoming an increasingly important mechanism for improving agent performance on real-world downstream tasks. However …
HuggingFacedaily curated papers2026-05-28
COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation [28]
Tianyi Zhou, Dongrui Liu, Leitao Yuan, Jing Shao, Xia Hu
LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and interaction style …
HuggingFacedaily curated papers2026-05-29
Task-Focused Memorization for Multimodal Agents [29]
Tao Zou, Yichen He, Tian Qiu, Yuan Lin, Hang Li
Long-term memory is essential for multimodal agents to build coherent experience, accumulate world knowledge, and achieve continual learning. However …
HuggingFacedaily curated papers2026-05-29
SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer [30]
Yuyang Zhao, Yicheng Pan, Qiyuan He, Jincheng Yu, Junsong Chen
Real-time streaming video-to-video editing (V2V) is critical for interactive applications such as live broadcasting and gaming, yet it remains a formidable challenge due to the stringent requirements for temporal consistency and inference …
HuggingFacedaily curated papers2026-05-28
dMoE: dLLMs with Learnable Block Experts [31]
Sicheng Feng, Zigeng Chen, Gongfan Fang, Xinyin Ma, Xinchao Wang
Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive models, offering competitive performance while naturally supporting parallel decoding. However …
HuggingFacedaily curated papers2026-05-29
MAAT: Multi-phase Adapter-Aware Targeted Unlearning [32]
Suryash Yagnik, Shubham Gaur, Saksham Thakur, Vinija Jain, Aman Chadha
Machine unlearning evaluation is structurally skewed: Why-type questions, which probe causal and relational knowledge, comprise less than 0.06% of CounterFact, 0.6% of ZSRE, and less than 1.3% of TOFU, MUSE, and WMDP-Cyber …
HuggingFacedaily curated papers2026-05-28
Not All Disagreement Is Learnable: Token Teachability in On-Policy Distillation [33]
Yuanyi Wang, Su Lu, Yanggan Gu, Pengkai Wang, Yifan Yang
On-policy distillation (OPD) trains a student on its own rollouts with token-level teacher supervision. Recent selective OPD methods exploit the non-uniformity of OPD signals by prioritizing high-entropy or high-disagreement tokens. …
HuggingFacedaily curated papers2026-05-26
GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration [34]
Xiangtao Kong, Jixin Zhao, Lingchen Sun, Rongyuan Wu, Lei Zhang
Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail to model real-world degradations …
HuggingFacedaily curated papers2026-05-29
Linear Scaling Video VLMs for Long Video Understanding [35]
Cristobal Eyzaguirre, Jiajun Wu, Juan Carlos Niebles
Video vision-language models (VLMs) are increasingly used in long-horizon and streaming settings, yet most video encoders still rely on spatiotemporal self-attention …
HuggingFacedaily curated papers2026-05-29
Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models [36]
Jiacheng Lu, Haoyi Zhu, Sipei Yi, Enze Xie, Yu Li
Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time game simulation, virtual scene navigation, and embodied AI training. However …
HuggingFacedaily curated papers2026-05-29
Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models [37]
Jiazheng Xing, Hangjie Yuan, Lingling Cai, Xinyu Liu, Yujie Wei
Connector-based video unified models have demonstrated strong capability in instruction-grounded video synthesis, but integrating a large high-fidelity generator into the unified training loop is computationally prohibitive …
HuggingFacedaily curated papers2026-05-29
From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors [38]
Jiejun Tan, Zhicheng Dou, Xinyu Yang, Yuyang Hu, Yiruo Cheng
LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. In local agentic harnesses, an LLM can read and write files, call tools, and reuse workspace state across sessions. …
HuggingFacedaily curated papers2026-05-29
LongTraceRL: Learning Long-Context Reasoning from Search Agent Trajectories with Rubric Rewards [39]
Nianyi Lin, Jiajie Zhang, Lei Hou, Juanzi Li
Long-context reasoning remains a central challenge for large language models, which often fail to locate and integrate key information in extensive distracting content …
HuggingFacedaily curated papers2026-05-29
Representation Forcing for Bottleneck-Free Unified Multimodal Models [40]
Yuqing Wang, Zhijie Lin, Ceyuan Yang, Yang Zhao, Fei Xiao
Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrained VAE for image generation, imposing a structural bottleneck. …
HuggingFacedaily curated papers2026-05-29
VLM3: Vision Language Models Are Native 3D Learners [41]
Zhipeng Cai, Zhuang Liu, Yunyang Xiong, Zechun Liu, Vikas Chandra
Vision Language Models (VLMs) enable a unified model to solve various vision tasks through prompting. They have shown promising performance in semantic understanding. …
HuggingFacedaily curated papers2026-05-28
Exploring Autonomous Agentic Data Engineering for Model Specialization [42]
Yujie Luo, Xiangyuan Ru, Jingsheng Zheng, Jingjing Wang, Yuqi Zhu
Large Language Models (LLMs) have demonstrated strong performance on general tasks, while often struggling to adapt to specialized domains without high-quality domain-specific data …
HuggingFacedaily curated papers2026-05-28
Function2Scene: 3D Indoor Scene Layout from Functional Specifications [43]
Ruiqi Wang, Qimin Chen, Daniel Ritchie, Angel X. Chang, Manolis Savva
Most text-driven 3D indoor scene synthesis methods generate rooms from object-centric prompts, asking what furniture should be placed rather than how the space is used. Yet in real interior design …
HuggingFacedaily curated papers2026-05-29
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring [44]
Seongheon Park, Wendi Li, Changdae Oh, Samuel Yeh, Zsolt Kira
Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnerable to execution failures that compromise reliability in real-world deployment …
HuggingFacedaily curated papers2026-05-29
LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis [45]
Kewei Xu, Xiaoben Lu, Shuofei Qiao, Zihan Ding, Haoming Xu
Real-world data analysis is inherently iterative, yet existing benchmarks mostly evaluate isolated or short interactive tasks, leaving agents' ability to track evolving analytical context over long horizons untested. We introduce LongDS …
HuggingFacedaily curated papers2026-05-28

🔗 All Sources

  1. It's Not Just X. It's Y
  2. On Reading SRAMs in IR Images, and Establishing Bounds on Trust
  3. ChatGPT Won't Let You Type Until Cloudflare Reads Your React State. I Decrypted the Program That Does It
  4. Early identification of breakthrough technologies: Insights from science-driven innovations
  5. Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements
  6. Artificial intelligence and machine learning in cybersecurity: a deep dive into state-of-the-art techniques and future paradigms
  7. Securing the future: exploring post-quantum cryptography for authentication and user privacy in IoT devices
  8. Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements
  9. SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones?
  10. Emergent Languages in Populations of Language Model Agents: From Token Efficiency to Oversight Evasion
  11. PEEK: Picking Essential frames via Efficient Knowledge distillation
  12. iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning
  13. Benchmarking Composed Image Retrieval for Applied Earth Observation
  14. DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
  15. Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents
  16. Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)?
  17. SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks
  18. The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement
  19. Count Anything
  20. AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling
  21. The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
  22. Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal
  23. Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios
  1. Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer
  2. SwanVoice: Expressive Long-Form Zero-Shot Speech Synthesis for Both Monologue and Dialogue
  3. FRAPPE: Full Input, Residual Output Autoencoding with Projection Pursuit Encoder
  4. OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents
  5. COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation
  6. Task-Focused Memorization for Multimodal Agents
  7. SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer
  8. dMoE: dLLMs with Learnable Block Experts
  9. MAAT: Multi-phase Adapter-Aware Targeted Unlearning
  10. Not All Disagreement Is Learnable: Token Teachability in On-Policy Distillation
  11. GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration
  12. Linear Scaling Video VLMs for Long Video Understanding
  13. Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models
  14. Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models
  15. From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors
  16. LongTraceRL: Learning Long-Context Reasoning from Search Agent Trajectories with Rubric Rewards
  17. Representation Forcing for Bottleneck-Free Unified Multimodal Models
  18. VLM3: Vision Language Models Are Native 3D Learners
  19. Exploring Autonomous Agentic Data Engineering for Model Specialization
  20. Function2Scene: 3D Indoor Scene Layout from Functional Specifications
  21. Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
  22. LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis
Generated by Hermes Agent • arXiv • Google Scholar • Lobste.rs • Hacker News • HuggingFace