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◬ AI & Machine Learning Jun 06, 2026
Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison

arXiv:2606.05436v1 Announce Type: new Abstract: Summarizing the latest medical literature to guide clinical decision-making is essential for evidence-based medicine and high-quality patient care. Yet …

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Zero knowledge verification for frontier AI training is possible

arXiv:2606.05433v1 Announce Type: new Abstract: Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion for designating high-impact models, but enforcem…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models

arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigi…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers

arXiv:2606.05420v1 Announce Type: new Abstract: The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven by the adoption of artificial intelligence, has raised concerns about…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
A Motivational Architecture for Conversational AGI

arXiv:2606.05411v1 Announce Type: new Abstract: Motivational architectures in cognitive AI have largely been designed for physical agents regulating bodily needs. Conversational agents operate in a di…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution

arXiv:2606.05408v1 Announce Type: new Abstract: When an LLM repeatedly mutates a program, does it explore new forms or circle back to the same ones? We study this question by analyzing LLM-driven muta…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Agents' Last Exam

arXiv:2606.05405v1 Announce Type: new Abstract: Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deploymen…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Harnessing Generalist Agents for Contextualized Time Series

arXiv:2606.05404v1 Announce Type: new Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, real-world practitioners often require end-to-end wo…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
LeanMarathon: Toward Reliable AI Co-Mathematicians through Long-Horizon Lean Autoformalization

arXiv:2606.05400v1 Announce Type: new Abstract: Long-horizon autoformalization of research mathematics fails not only at hard lemmas, but at scale: statements drift, dependencies tangle, context decay…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Residual Modeling for High-Fidelity Learned Compression of Scientific Data

arXiv:2606.05389v1 Announce Type: new Abstract: Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at m…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Stability vs. Manipulability: Evaluating Robustness Under Post-Decision Interaction in LLM Judges

arXiv:2606.05384v1 Announce Type: new Abstract: LLM-as-judge evaluation is widely used in benchmarking pipelines, where model outputs are compared and ranked using automated evaluators. These pipeline…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Synthetic Contrastive Reasoning for Multi-Table Q&A

arXiv:2606.05382v1 Announce Type: new Abstract: Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)

arXiv:2606.05357v1 Announce Type: new Abstract: Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction wit…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
SentinelBench: A Benchmark for Long-Running Monitoring Agents

arXiv:2606.05342v1 Announce Type: new Abstract: AI agents are increasingly asked to carry out work that spans minutes, hours, or longer. Yet the default model of agent behavior is continuous action: i…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory

arXiv:2606.05334v1 Announce Type: new Abstract: Returned products in circular factories re-enter production with heterogeneous degradation states, usage histories, and remaining capability. Reuse cann…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
GITCO: Gated Inference-Time Context Optimization in TSFMs

arXiv:2606.05332v1 Announce Type: new Abstract: Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and s…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition

arXiv:2606.05316v1 Announce Type: new Abstract: Multimodal memes are dynamic and often require up to date background knowledge for interpretation. Existing methods often overlook such knowledge or rel…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
What Should Agents Say? Action-state Communication for Efficient Multi-Agent Systems

arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized around roles, pipelines, and turn schedules, while the content that age…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment

arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown,…

arXiv AI Read →
◬ AI & Machine Learning Jun 06, 2026
Thousand Token Wood: shipping a multi-agent economy on a 3B model
Hugging Face Read →
◬ AI & Machine Learning Jun 05, 2026
The latest AI news we announced in May 2026

Here are Google’s latest AI updates from May 2026

Google AI Read →
◬ AI & Machine Learning Jun 05, 2026
The Meta hack shows there’s more to AI security than Mythos

On June 5, 404 Media reported that attackers had been using Meta’s AI customer support agent to steal Instagram accounts. Their approach was simple: They asked the agent to link the accounts to email …

MIT Tech Review AI Read →
◬ AI & Machine Learning Jun 05, 2026
Cheating in Multiplayer Online Games: a Dataset

arXiv:2606.06013v1 Announce Type: new Abstract: Cheating poses a significant threat to the Multiplayer Online Games (MOG) industry by degrading player satisfaction and undermining the fairness in comp…

arXiv Security Read →
◬ AI & Machine Learning Jun 05, 2026
AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction pooling

arXiv:2606.05986v1 Announce Type: new Abstract: Existing learning-based detectors for Solidity smart-contracts reduce vulnerability detection to syntactic pattern matching within single functions, yet…

arXiv Security Read →
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