AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchNarrative Paradoxes in LLM Inference: Shaping Reasoning Trajectories toward Misalignment
arXiv:2610.16312v1 Announce Type: new Abstract: Explicit reasoning in large language models (LLMs) is often associated with reliability, yet it can still pose risks when a model infers harmful goals under a benign contex…
- arXiv cs.AIagentsReTAC: Residual Test-Time Agentic Computation for Video Spatial Reasoning
arXiv:2610.16315v1 Announce Type: new Abstract: Test-time agentic computation can improve multimodal large language models (MLLMs) through planning, tool use, iterative perception, and reflection, but indiscriminate comp…
- arXiv cs.AIagentsHyWe: Unifying Search and Operation for Real-World Hybrid Web Tasks
arXiv:2610.16319v2 Announce Type: replace Abstract: Real-world hybrid web tasks need both information gathering and page interaction, yet search-based and operation-based agents are developed and evaluated separately. To…
- arXiv cs.AIresearchWhen a Conceptor Complement Becomes Gain: Operator Geometry and Behavioral Attribution in Language Models
arXiv:2610.16325v1 Announce Type: new Abstract: When a steering intervention changes a language model's behavior, which part of the intervention deserves the credit? We test this question for a target-centered, scaled co…
- arXiv cs.AIagentsTRAP: Tool-result Replay Attack for Probing Misbinding in LLM Agents
arXiv:2610.16333v1 Announce Type: new Abstract: As AI agents increasingly act through external tools, tool results are no longer simple outputs but execution artifacts that must remain correctly associated with the conte…
- arXiv cs.AIagentsEfficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate
arXiv:2610.16343v1 Announce Type: new Abstract: Multi-agent debate has shown promise for improving the reasoning of large language models, yet recent theory suggests its benefits are highly regime-dependent. While intera…
- arXiv cs.AIresearchChronoScribe: Semantic-Numerical Specialization for Instruction-Driven Time Series Forecasting
arXiv:2610.16345v1 Announce Type: new Abstract: Recent advances in instruction-driven time series forecasting highlight a fundamental tension: systems must simultaneously master natural-language instruction following and…
- arXiv cs.AIresearchWorld Models Need a Physical Registry: Learning Internal Predictive States for Physically Plausible World Models
arXiv:2610.16365v1 Announce Type: new Abstract: Video world models must generate physically plausible futures, not just realistic frames. Existing approaches typically use semantic, physical, or predictive information to…
- arXiv cs.AIresearchRetroPlanner: Multi-Route Expansion and Multi-Objective Reasoning for LLM-Based Retrosynthesis Planning
arXiv:2610.16391v1 Announce Type: new Abstract: Multi-step retrosynthesis planning is often considered solved once a route to purchasable starting materials is found, but such a route should also be practical in real-wor…
- arXiv cs.AIagentsRecursive Environment Scaling for General Long-Horizon Agents
arXiv:2610.16397v2 Announce Type: replace Abstract: We study environment scaling as a way to increase agent-benchmark difficulty while holding core task objectives fixed. Our framework, Recursive Environment Scaling (RES…
- arXiv cs.AIagentsEvoWeb: A Benchmark for Coding Agents on Evolving Web Applications
arXiv:2610.16402v1 Announce Type: new Abstract: Web application development often proceeds through successive requests that extend an existing implementation. Yet web-generation benchmarks primarily evaluate development…
- arXiv cs.AIagentsSLS-Bench: A Benchmark for Incident Log Summarization with Synthetic Observability Data
arXiv:2610.16412v1 Announce Type: new Abstract: As IT systems grow in complexity, automated agent-driven incident response becomes increasingly critical. A key capability for these agents is summarizing large log streams…
- arXiv cs.AIresearchChain Dimension Scaling: Communication-Efficient Loop-Style Scaling for Industrial Short-Video Ranking
arXiv:2610.16415v1 Announce Type: new Abstract: Industrial recommendation rankers keep scaling in width and depth to billions of parameters, but this increasingly incurs costs in parameter growth, distributed communicati…
- arXiv cs.AIagentsAuthGateBench: Benchmarking LLMs as Authorization Gate
arXiv:2610.16426v1 Announce Type: new Abstract: Automated approval systems let coding agents execute high-risk actions with minimal human oversight by delegating the authorization decision to a classifier, typically a la…
- arXiv cs.AIresearchRAP-WAM: Learning World-Action Models through Predictive Rehearsal and Action Perturbations
arXiv:2610.16443v2 Announce Type: replace Abstract: Recent world action models draw on video generation priors to jointly predict future observations and robot actions. Adapting these priors to control requires determini…
- arXiv cs.AIagentsXAI-Guided Fourier Domain Generalisation for Pure-Simulation Sim-to-Real Deep Reinforcement Learning
arXiv:2610.16478v1 Announce Type: new Abstract: Deep reinforcement learning has shown strong potential for vision-based autonomous driving, but policies trained in simulation often suffer severe performance degradation w…
- arXiv cs.AIresearchPXRD-Bench: How Close Are We to Determining Crystal Structures from Powder Diffraction?
arXiv:2610.16480v1 Announce Type: new Abstract: Determining crystal structures from powder X-ray diffraction (PXRD) would enable routine characterization of newly synthesized materials, including those absent from refere…
- arXiv cs.AIresearchBoosting the Learning for Ranking Patterns
arXiv:2610.16511v1 Announce Type: new Abstract: Pattern mining is a valuable tool for exploratory data analysis, but identifying relevant patterns for a specific user is challenging. Various interestingness mea- sures ha…
- arXiv cs.AIagentsEAU: Environment-Agent-User Co-evolution for Training User-Centric Agents
arXiv:2610.16523v1 Announce Type: new Abstract: Training LLM agents to interact with users over multiple turns is challenging because the learning signal depends not only on the agent, but also on the user simulator and…
- arXiv cs.AIresearchDoes the Explanation Drift Before the Guarantee? Label-Free Early Warning on Evolving Graphs
arXiv:2610.16534v1 Announce Type: new Abstract: Deployed models can fail silently as the world they describe evolves. Attribution drift has served as an early warning in tabular data; we ask whether, in graph streams, a…
- arXiv cs.AIagentsOvertaught, Underlearned: Learner-Centered Distillation from Multi-Agent Discussion
arXiv:2610.16543v1 Announce Type: new Abstract: Multi-agent discussion produces reasoning collaboratively, while deployment still relies on a smaller student that must answer alone. Full-graph distillation transfers such…
- arXiv cs.AIresearchMaking Language the Low-Rate Code of Vision: Successive Refinement from Words to Pixels
arXiv:2610.16552v1 Announce Type: new Abstract: An ordered visual code lets a short prefix stand in for an image, and the training loss decides what that prefix contains. Under pixel reconstruction the first bits go to t…
- arXiv cs.AIresearchAI Discovery in Combinatorics: From Problems to Solutions and Back to Bigger Problems
arXiv:2610.16555v1 Announce Type: new Abstract: We introduce $qt$Bench, a benchmark of 29 open problems in algebraic combinatorics. These problems ask for a simple combinatorial algorithm that explains given polynomial c…
- arXiv cs.AIagentsG$^2$WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation
arXiv:2610.16558v1 Announce Type: new Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies beyond the current field…
- arXiv cs.AIresearchDouble-Rollout Reinforcement Learning with Sampling-based Reward Estimation
arXiv:2610.16593v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) implemented with Group Relative Policy Optimization (GRPO) has driven substantial progress in training reasoning langu…
- arXiv cs.AIresearchWhen 1+1 Backfires: Rethinking Relevance-Diversity Balancing for Sample-Aware Visual Token Reduction
arXiv:2610.16615v1 Announce Type: new Abstract: Visual token compression has emerged as a critical technique for reducing the inference cost of Vision-Language Models. Existing methods select tokens based on text relevan…
- arXiv cs.AIresearchWeak Segmentation-Guided GAN for~Realistic Color Edition
arXiv:2610.16620v1 Announce Type: new Abstract: Editing the color of images in a realistic way finds many applications such as changing the perception of an image, data augmentation or film post processing. The design of…
- arXiv cs.AIresearchLATCH: LLM-Assisted Timing Closure Harness for Post-Route FPGA Optimisation
arXiv:2610.16625v1 Announce Type: new Abstract: Post-route FPGA timing closure remains expert-dependent and computationally expensive. We present LATCH (LLM-Assisted Timing Closure Harness), a two-layer framework that se…
- arXiv cs.AIresearchDoes a Hosted Decision Model Respect Irrelevant Alternatives? A Pre-Registered Test of Option-Set Dependence in Jev
arXiv:2610.16655v1 Announce Type: new Abstract: Decision APIs that return a probability for each option are routinely used as if those probabilities were properties of the options themselves. That reading is valid only i…
- arXiv cs.AIagentsStructural Baselines Matter for Agent Failure Detection and Attribution
arXiv:2610.16661v1 Announce Type: new Abstract: An LLM agent using tools can fail silently. It stops before the task is done, raises no error, and answers fluently. Two kinds of monitor address this, one deciding whether…
- arXiv cs.AIagentsTrace-to-Architecture: Capability Bottleneck Diagnosis for Harness Revision
arXiv:2610.16725v1 Announce Type: new Abstract: Improving an LLM agent requires knowing what to change when it fails. Similar failures can require different fixes, and resolving one problem can expose another. We introdu…
- arXiv cs.AIresearchQueue-Aware Token Communications: Bridging AI Representation and Wireless Service
arXiv:2610.16730v1 Announce Type: new Abstract: The rapid advancement of foundation models and edge intelligence is transforming wireless networks from data-oriented communication systems into artificial intelligence (AI…
- arXiv cs.AIresearchSeparating Prompt Harmfulness from Interaction Safety via Partial Generation
arXiv:2610.16761v1 Announce Type: new Abstract: LLM-based information systems need safety guardrails. Most guardrails classify the prompt alone. If the prompt looks harmful, the system rejects it before any answer is gen…
- arXiv cs.AIresearchGeospatial Vector Geometry as a Native Spatial Modality for Vision-Language Models
arXiv:2610.16769v1 Announce Type: new Abstract: Geospatial reasoning links VLMs to real-world action and decision making. Reliable reasoning requires accurate spatial information and effective spatial representations. Ho…
- arXiv cs.AIagentsGame-Creation-Agents: Autonomous Game Production
arXiv:2610.16776v1 Announce Type: new Abstract: Game-Creation-Agents (GCA) turns a natural-language request into a runnable Phaser 4 browser game. The pipeline first builds a multimodal game design document that couples…
- arXiv cs.AIresearchLIBERO-Industry: Benchmarking Robotic Manipulation under Industrial Process Constraints
arXiv:2610.16782v2 Announce Type: replace Abstract: Industrial manipulation in flexible manufacturing, e.g., high-mix, low-volume (HMLV) electronics assembly, requires robot policies to adapt to changing products and pro…
- arXiv cs.AIagentsSame Operation, Different Permission: Evaluating Whether Guardrails Honor Authorization
arXiv:2610.16838v1 Announce Type: new Abstract: As language-model agents write code, move money and change records on behalf of users, deciding whether an action is authorized has become a central safety problem. Guardra…
- arXiv cs.AIresearchCLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation Objectives
arXiv:2610.16876v2 Announce Type: replace Abstract: Data selection turns large multimodal instruction pools into compact training subsets tailored to a vision-language model's target capabilities. Effective selection req…
- arXiv cs.AIagentsAcceptable Misalignment
arXiv:2610.16881v1 Announce Type: new Abstract: There is a specific challenge designers face in developing autonomous robots capable of open-ended learning. This challenge is how one can develop such systems in an ethica…
- arXiv cs.AIresearchTransparency as Answerability: Role-Dependent Information Flow Modeling
arXiv:2610.16887v1 Announce Type: new Abstract: Transparency in AI-supported decision systems is widely required but poorly defined. Existing approaches treat transparency as a property of systems or components, producin…
- arXiv cs.AIagentsObserve, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration
arXiv:2610.16895v1 Announce Type: new Abstract: LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating a collaborator's acti…
- arXiv cs.AIagentsNeural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty
arXiv:2610.16902v1 Announce Type: new Abstract: Bayesian Networks (BNs) are established tools for letting agents reason under uncertainty in sequential decision-making. They split a joint distribution into local conditio…
- arXiv cs.AIagentsAudit tools of the trade: Automated Auditor Elicitation Can Be Sensitive to the Context the Auditor Is Given
arXiv:2610.16911v1 Announce Type: new Abstract: Does providing additional context to automated AI auditors improve their effectiveness? Using the Petri tool to audit LLM coding agents, we test the impact of providing two…
- arXiv cs.AIresearchTransparent Information Flow Modeling for Role-Aware AI Act Assessment
arXiv:2610.16916v1 Announce Type: new Abstract: The European Union's Artificial Intelligence Act introduces a structured framework for governing high-risk AI systems, emphasizing transparency, risk management, and role-s…
- arXiv cs.AIresearchWeFair: Fidelity-Aware Alignment from Human Feedback for Personalized Query Rewriting in Short-Video Search
arXiv:2610.16927v2 Announce Type: replace Abstract: Short-video search needs compact query rewriters that recover users' personalized intent from ambiguous queries under strict latency constraints. Existing LLM-based met…
- arXiv cs.AIagentsMADDIE: Multi-Agent Drug Discovery Engine
arXiv:2610.16975v3 Announce Type: replace Abstract: Drug discovery remains a resource-intensive and time-consuming process, involving billions of dollars and a decade of development to advance a drug to market. While man…
- arXiv cs.AIagentsPRAISE: A Reproducible Workflow for Non-Programmer Scientists to Implement Published AI Models
arXiv:2610.16980v1 Announce Type: new Abstract: Artificial Intelligence (AI) models are increasingly developed, published and used across scientific fields. Researchers, students and industry professionals who want to ap…
- arXiv cs.AIagentsGlasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents
arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source agents remains chal…
- arXiv cs.AIresearchUnderstanding Personalization Gains in Whisper ASR
arXiv:2610.17019v2 Announce Type: replace Abstract: Whisper-style ASR models provide strong zero-shot transcription, but their residual errors are not evenly distributed across datasets, recording conditions, and metadat…
- arXiv cs.AIresearchBenchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints
arXiv:2610.17027v1 Announce Type: new Abstract: Detecting credit card fraud is notoriously difficult because fraudulent charges make up less than 0.2% of total transactions. Quantum Machine Learning (QML), particularly Q…