AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchAtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution
arXiv:2609.31133v3 Announce Type: replace Abstract: High-fidelity atomistic evolution over long timescales requires more than observing the current crystal configuration. Instantaneous atomistic snapshots are often incom…
- arXiv cs.AIagentsToward AI-Augmented Cooperative Engineering Workflows: Requirements and Architecture the European Rover Challenge
arXiv:2609.31136v1 Announce Type: new Abstract: The growing availability of Artificial Intelligence (AI) tools creates new opportunities to support engineering design processes, yet their current use often remains limite…
- arXiv cs.AIresearchCan Linguistic Reasoning Vectors Enhance Multimodal Reasoning Ability?
arXiv:2609.31140v1 Announce Type: new Abstract: Most Vision-Language Models (VLMs) are built by extending pretrained Large Language Models (LLMs) with visual modules and multimodal alignment. However, this multimodal sca…
- arXiv cs.AIagentsMomentum-Guided Federated Split Distillation for Personalized Temporal Edge Intelligence
arXiv:2609.31159v1 Announce Type: new Abstract: We propose a momentum-guided federated split distillation framework for personalized, efficient, and autonomous temporal edge intelligence. We introduce TeRR-SAtt, our nove…
- arXiv cs.AIresearchNeural State Prediction: Obstructing Shortcut Learning in EEG Foundation Models
arXiv:2609.31167v1 Announce Type: new Abstract: EEG foundation models increasingly use masked prediction to learn from unlabeled recordings, but optimizing this objective does not ensure transferable neural representatio…
- arXiv cs.AIagentsSemantic Navigation for Issue Localization in Code Repository
arXiv:2609.31176v1 Announce Type: new Abstract: Repository-level issue localization aims to identify and rank the files and functions relevant to resolving a reported issue. LLM agents approach this task iteratively: the…
- arXiv cs.AIresearchSPO: Discovering Adaptive Large Neighborhood Search Operators via Stackelberg Program Optimization
arXiv:2609.31179v1 Announce Type: new Abstract: Large neighborhood search (LNS) relies critically on destroy and repair operators, whose effectiveness depends on both adaptation to the evolving LNS state and interaction…
- arXiv cs.AIresearchAccounting for Bias Enables Sustainable LLM Evaluation
arXiv:2609.31184v1 Announce Type: new Abstract: LLM-as-a-judge has become the de facto standard for scalable, subjective evaluation, yet current leaderboards compensate for systematic measurement bias by running ever mor…
- arXiv cs.AIagentsEvolutionary Safety of Recursive Self-Improving AI: Taxonomy, Risk Discovery, and Evaluation
arXiv:2609.31186v2 Announce Type: replace Abstract: Rapid advances in AI are bringing recursive self-improvement (RSI) closer to practice, with growing progress in model self-training, self-evolving agents, and automated…
- arXiv cs.AIresearchSamples, Sources, Space: Decomposing Data Scale in Spatially Structured Representation Learning of Human Brain Microarchitecture
arXiv:2609.31201v1 Announce Type: new Abstract: Scaling studies typically represent training data by a single count of samples. For hierarchically and spatially structured data, however, the same number of samples can be…
- arXiv cs.AIresearchWhich Influence Are We Estimating? The Role of Counterfactual Specifications in Data Attribution
arXiv:2609.31214v1 Announce Type: new Abstract: Estimating the influence of training examples on model behavior is essential for data debugging, valuation, and attribution. Existing influence estimators often produce inc…
- arXiv cs.AIresearchDIAL: Position-Debiased LLM Judges with Adaptive Human Preference Calibration
arXiv:2609.31215v1 Announce Type: new Abstract: Large language models (LLMs) as a judge enable scalable evaluation, but their judgments can be sensitive to response order and, even after removing such position effects, c…
- arXiv cs.AIresearchPurin: A Biology-inspired Mechanism for Artificial Neural Networks
arXiv:2609.31235v1 Announce Type: new Abstract: Artificial neural networks (ANNs) usually represent neural transmission with fixed trainable weights during a training batch, which omits short-term changes in synaptic eff…
- arXiv cs.AIagentsMA-WAM: Multi-Agent World-Action Model for Test-Time Planning
arXiv:2609.31281v1 Announce Type: new Abstract: Multi-agent cooperative tasks require different agents to execute a joint action simultaneously, and each agent's action affects both the observations and responses of the…
- arXiv cs.AIagentsG2MAF: Test-Time Gradient Guidance for Multi-Agent Flow Policies
arXiv:2609.31286v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) learns cooperative policies from fixed datasets without further environment interaction and a learned policy is frozen at…
- arXiv cs.AIresearchThe Right Information Extraction Pipeline Depends on the Document: Accuracy-Energy Trade-offs for Small, Local Models
arXiv:2609.31341v1 Announce Type: new Abstract: Whether an information extraction pipeline should process page images or parsed text depends on the document, and the answer flips across the layout spectrum. We study this…
- arXiv cs.AIresearchMutable Transcripts: Mitigating Context Pollution through Editable Conversation State
arXiv:2609.31354v1 Announce Type: new Abstract: Contemporary large language model (LLM) chat systems treat conversation history as an immutable sequence of turns that defines the model's working context. However, user in…
- arXiv cs.AIresearchPrograms-of-Layers in LLMs through the Lens of Cortical Areas
arXiv:2609.31360v1 Announce Type: new Abstract: Inference in LLMs is conventionally a fixed-depth, fixed-order forward pass through every layer, regardless of how difficult the input is. The human brain does not work thi…
- arXiv cs.AIagentsEvaluating Budgeted Context Projection with Unexecuted Companion Runs
arXiv:2609.31381v2 Announce Type: replace Abstract: Context projection can shorten individual requests while changing whether an agent finishes within its budget. We examine how sequential evaluation obscures this trade-…
- arXiv cs.AIagentsCompress What You See, Not What You Say: Anchored Context Distillation for Latent-Observation Software Engineering Agents
arXiv:2609.31430v1 Announce Type: new Abstract: Tool observations dominate the context of software-engineering agents, making long interaction histories costly to maintain. Existing context compression methods can discar…
- arXiv cs.AIagentsSegment-Level Agentic Topic Modeling for Improved Data Exploration and Resource Efficiency
arXiv:2609.31460v1 Announce Type: new Abstract: Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a variety of industry sec…
- arXiv cs.AIresearchGame Arena: Strategic LLM Evaluation in Competitive Environments
arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from static benchmarks, ga…
- arXiv cs.AIresearch"AI is (not) the new...": A Diagnostic Analogy Framework for Generative AI's Cultural Impacts
arXiv:2609.31482v1 Announce Type: new Abstract: Generative AI is reshaping the cultural infrastructures through which knowledge is found, synthesized, and held accountable. To make sense of this shift, scholars and polic…
- arXiv cs.AIresearchUQ-LOB: Uncertainty-Aware Limit Order Book Mid-Price Forecasting
arXiv:2609.31491v2 Announce Type: replace Abstract: Forecasting short-horizon mid-price movements from limit order book (LOB) data is central to algorithmic trading, yet most deep LOB forecasters are point predictors: th…
- arXiv cs.AIresearchPrompt Minimization: Reducing Input Redundancy Without Sacrificing Output Fidelity
arXiv:2609.31505v1 Announce Type: new Abstract: Despite the growing capabilities of large language models (LLMs), prompt design remains largely heuristic and ad hoc. This project will explore $\textit{prompt minimization…
- arXiv cs.AIresearchA Flow Matching Framework for Neural Representational Dissimilarity
arXiv:2609.31544v1 Announce Type: new Abstract: Neural representational dissimilarity quantifies differences between neural response distributions, and is essential for comparing neural codes across stimuli, brain areas,…
- arXiv cs.AIagentsMulti-agent Scaling Across Disjunctive and Compensatory Tasks
arXiv:2609.31563v1 Announce Type: new Abstract: Multi-agent LLM systems are often expected to improve as team size increases, yet the scaling behavior may depend on task structure. Our central contribution is to introduc…
- arXiv cs.AIagentsDeepEdu-v1: Efficient and Scalable Agentic LLMs for Vietnamese Education
arXiv:2609.31568v1 Announce Type: new Abstract: AI tutoring could markedly improve learning outcomes for students in developing regions such as Vietnam, yet the two obvious paths both fall short. Cloud assistants such as…
- arXiv cs.AIresearchLearning to Stop without Learning to Stop: Self-Supervised Confidence Training Improves Reasoning Efficiency
arXiv:2609.31619v1 Announce Type: new Abstract: Reasoning models often generate very long reasoning traces, making inference computationally expensive. Existing approaches typically improve efficiency either through infe…
- arXiv cs.AIresearchENAS: An Efficient Hardware-Aware Neural Architecture Search Framework for TinyML on Resource-Constrained Microcontrollers
arXiv:2609.30272v1 Announce Type: cross Abstract: We present \textbf{ENAS}, a hardware-aware Neural Architecture Search (NAS) framework that combines a static feasibility check, a cell-based search space supporting stand…
- arXiv cs.AIresearchWhen Does Advection-Aware Graph Nowcasting Help? A Controlled Study of Distributed Solar Ramp Forecasting with a Self-Supervised Cloud-Motion Estimator
arXiv:2609.30286v1 Announce Type: cross Abstract: Short-term forecasting of cloud-induced power ramps across a network of distributed photovoltaic (PV) or irradiance sensors is a recognised pain point for grid operators.…
- arXiv cs.AIresearchA Mechanistic Study of AI-Text Detection Neurons in Frozen BERT: Sparse Probing and Activation Patching on RAID
arXiv:2609.30287v1 Announce Type: cross Abstract: AI-generated text detectors achieve high accuracy on standard benchmarks, yet the internal representations that drive these predictions remain poorly understood. We study…
- arXiv cs.AIresearchA Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models
arXiv:2609.30292v1 Announce Type: cross Abstract: Online reviews shape consumer decisions, platform governance, and corporate reputation.Fake reviews compromise this information channel by injecting deceptive evidence in…
- arXiv cs.AIagentsCartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents
arXiv:2609.30293v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) enables AI agents to discover and call tools, but loading every definition becomes expensive as connected catalogs grow. We present Carto…
- arXiv cs.AIresearchSlideLab: Audience-Centered Scientific Slide Generation and Evaluation
arXiv:2609.30294v2 Announce Type: replace-cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clearly, and hel…
- arXiv cs.AIresearchSignTrace: Describe a Sign, Find the Word
arXiv:2609.30295v1 Announce Type: cross Abstract: Identifying an unfamiliar sign is difficult when a learner remembers its movement but does not know its meaning or formal feature codes. SignTrace addresses this longstan…
- arXiv cs.AIagentsBootstrapping Conversational Recommendation Agents At Spotify: Synthetic Data Generation and Self-Improvement Loops
arXiv:2609.30297v1 Announce Type: cross Abstract: Conversational recommendation agents are a new paradigm for content discovery, enabling users to express complex intents through natural language (e.g., "recommend Italia…
- arXiv cs.AIagentsWhat Will Remain Human in Software Architecture? A Focus Group Report
arXiv:2609.30334v1 Announce Type: cross Abstract: AI development agents are increasingly used to support and partially automate software architecture tasks. To explore how practitioners perceive this shift, specifically…
- arXiv cs.AIagentsCoding Agents Aren't Enough! Evaluating an Enterprise Security Brain for Agentic Cloud Investigations
arXiv:2609.30345v2 Announce Type: replace-cross Abstract: Cloud-security investigation is dominated by population tasks: which identities can read a data store, how many resources fail a control, what is reachable from a…
- arXiv cs.AIresearchAdaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices
arXiv:2609.30348v1 Announce Type: cross Abstract: Gaussian processes constitute a cornerstone of probabilistic machine learning, yet scaling them to large datasets typically forces a trade-off between computational effic…
- arXiv cs.AIresearchStrategic Self-Consistency
arXiv:2609.30352v1 Announce Type: cross Abstract: Self-consistency has become a popular technique for enhancing the reasoning abilities of large language models by generating multiple reasoning paths and selecting the fi…
- arXiv cs.AIresearchCost-Aware Best-LLM Identification using Dueling Feedback
arXiv:2609.30360v1 Announce Type: cross Abstract: Inspired by the problem of identifying the best model from a collection of large language models (LLMs) with heterogeneous querying costs, we formulate and analyse a vari…
- arXiv cs.AIresearchDanLing NestedTensor: Composable Multi-Ragged Tensors for Deep Learning
arXiv:2609.30379v1 Announce Type: cross Abstract: Variable-size inputs are common in deep learning, but dense batching allocates a shared envelope and spends computation on padding. The cost multiplies across varying axe…
- arXiv cs.AIresearchWhat Improves Multimodal Misinformation Detection? Answers from a Large-Scale Empirical Study
arXiv:2609.30402v1 Announce Type: cross Abstract: Multimodal misinformation is increasingly crafted to look convincing by pairing a textual claim with an image that appears to "prove" it. Yet in practice, building effect…
- arXiv cs.AIresearchA Unified Account of Concepts and Chunks
arXiv:2609.30414v2 Announce Type: replace-cross Abstract: Cognitive psychology has studied how people encode, use, and learn concepts that describe categories, and how they represent, recognize, and acquire chunks for fa…
- arXiv cs.AIresearchUnderstanding Perturbed Parameter Ensemble Sensitivities Using A Contrastive Learning Approach
arXiv:2609.30420v1 Announce Type: cross Abstract: Perturbed parameter ensembles (PPEs) reveal how physics parameters affect climate simulations, but interpreting parameter sensitivities across multivariate, spatially str…
- arXiv cs.AIresearchActively Resolving Contextual Uncertainty for Underspecified Tasks in Natural Language
arXiv:2609.30428v1 Announce Type: cross Abstract: Foundation models provide robots with the ability to interpret natural language and reason about environmental context, yet most language-conditioned policies assume that…
- arXiv cs.AIresearchA Benchmarking Framework for Context-aware XR Interfaces
arXiv:2609.30466v1 Announce Type: cross Abstract: Everyday Extended Reality (XR) systems aim to provide context-aware access to the right functionalities at the right time and place, with minimal manual reconfiguration a…
- arXiv cs.AIagentsCARGO: Context-Aware Retrieval-Gated Evaluation of Agentic AI in Production
arXiv:2609.30471v1 Announce Type: cross Abstract: Reference-based LLM-as-a-judge evaluation assumes the reference answer is the target. In deployed agentic systems that operate over dynamic entities (support cases, asset…
- arXiv cs.AIresearchBreaking Homogeneity: Diversifying Persona Sets for Creative LLM Outputs
arXiv:2609.30492v1 Announce Type: cross Abstract: Language models often produce homogeneous responses to open-ended tasks; such homogeneity can spawn groupthink-the convergence of ideas toward a singular and potentially…