All Articles
19252 articles total
FlexMS: A Unified Public Benchmark for Molecule Tandem Mass Spectrum Prediction
Introduces FlexMS, a standardized public benchmark for predicting molecule tandem mass spectra to ensure fair architectural comparisons in metabolomics.
Generative AI for Managerial Decision-Making under Ambiguity and Sycophancy
A study on how Generative AI handles ambiguity and sycophancy in managerial decision-making, highlighting the need for human oversight.
An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
Analyzes the performance gap between joint and modular reinforcement learning for job shop scheduling with transportation resources in manufacturing.
PRISM: Perception Reasoning Interleaved for Sequential Decision Making
Introduces PRISM, a framework that couples perception and decision-making for embodied agents using a dynamic question-answer pipeline between VLMs and LLMs.
AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning
Presents AdaTKG, a method for temporal knowledge graph reasoning that uses adaptive per-entity memory updated via exponential moving averages.
Sundar Pichai faces boos, walkout at Stanford graduation ceremony over Google’s Israel, ICE ties
Sundar Pichai faced protests and boos during a Stanford graduation ceremony over Google's defense contracts and ties to Israel and ICE.
Key mission for Europe's commercial space enterprise scrubbed again
Isar Aerospace has faced multiple delays in its commercial space missions due to a lack of flight experience.
Giving AI a Headache: Acoustic Adversarial Attacks to Computer Vision Applications
Researchers demonstrate that audible acoustic frequencies can cause camera vibrations that lead to misclassifications in AI computer vision models like YOLO11.
CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification
CottonLeafVision is a deep learning framework using DenseNet201 and Grad-CAM to accurately classify and detect cotton leaf diseases.
Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit
This research explores the theoretical necessity of generating 'trivial' mathematical statements when using AI and proof assistants to discover valuable mathematics.
Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning
The PCMA framework is proposed for multi-objective multi-agent reinforcement learning to coordinate agent-specific preferences and improve team performance.
ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning
ClinHallu is a benchmark for diagnosing stage-wise hallucinations in medical multimodal LLMs, providing a structured reasoning trace for better diagnosis.
Learning optimal policies from event logs through reinforcement learning: a comparison of deep and MDP-based approaches
A comparison of deep RL and MDP-based approaches for learning optimal behavioral policies from historical event logs in process mining.
ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins
ANSR-DT is a neuro-symbolic framework for industrial digital twins that combines CNN-LSTM, Prolog-based reasoning, and PPO for adaptive and explainable decisions.
LLM-Powered AI Agent Systems and Their Applications in Industry
A comprehensive review of the evolution, architectures, and industrial applications of LLM-powered AI agent systems, including current challenges and solutions.
An O(x)Caml book that runs
A discussion or announcement regarding an OCaml book that is interactive or executable.
When Errors Become Narratives: A Longitudinal Taxonomy of Silent Failures in a Production LLM Agent Runtime
A study on 'silent failures' in production LLM agent runtimes, identifying a 'fail-plausible' pattern where LLMs hallucinate narratives instead of reporting errors.
AudioDER: A Deduplication-Enhanced Reasoning Dataset for Post-Training Large Audio-Language Models
Introduction of AudioDER, a deduplicated reasoning-oriented dataset designed to improve the post-training of Large Audio-Language Models (LALMs).
Regulating the Machine Contributor: Governance and Policy Alignment in Open Source
An analysis of AI-driven contributions to open-source projects, proposing a governance framework to align autonomous agents with existing community policies.
A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health
A comparative study of deep learning architectures for behavioral forecasting in mobile health, finding that PatchTST and TimesFM are particularly effective.