AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchTranscriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies
arXiv:2610.03693v1 Announce Type: new Abstract: Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete response (pCR) to neoa…
- arXiv cs.AIresearchIntentCoding: Amplifying User Intent in Code Generation
arXiv:2602.00066v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong capabilities in code generation, but their adherence to fine-grained user intent with multiple constraints remains a signif…
- arXiv cs.AIresearchMulti-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework
arXiv:2606.26567v1 Announce Type: cross Abstract: High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challenging due to the proh…
- arXiv cs.AIagentsClarifyCodeBench: Evaluating LLMs on Clarifying Ambiguous Requirements for Code Generation
arXiv:2607.00711v2 Announce Type: cross Abstract: Large Language Models have emerged as programming assistants. However, the efficacy of code generation is constrained by the quality of input requirements, which are freq…
- arXiv cs.AIresearchGlanceWAM: Sparse Test-Time Imagination for World-Action Models
arXiv:2608.23927v3 Announce Type: replace-cross Abstract: Video generative models provide rich physical priors for robot learning, yet existing world-action models (WAMs) face a fundamental trade-off: synchronous video g…
- arXiv cs.AIagentsCONTRA: Discovering and Qualifying Behavior-Changing Questions for Selective Clarification in LLM Code Generation
arXiv:2610.01769v1 Announce Type: cross Abstract: Coding agents can generate code that appears correct but implements behavior the user never intended. This mismatch can arise when an agent silently resolves underspecifi…
- arXiv cs.AIresearchCausal discovery identifies pathways linking physical activity to dementia risk in the UK BioBank
arXiv:2610.02221v1 Announce Type: cross Abstract: Physical Activity (PA) is consistently associated with lower risk of dementia, yet the mechanism linking PA to dementia prevention remain incomopletely understood. Here,…
- arXiv cs.AIresearchOne Distribution, Two Channels: Coverage-Calibrated KV Retention and Compensation
arXiv:2610.02235v2 Announce Type: replace-cross Abstract: Long-context decoding is increasingly constrained by key--value (KV) cache memory and bandwidth. Existing fixed-budget compression methods typically separate rete…
- arXiv cs.AIresearchHardware-Native Joint Sparse-Quantization for Trillion-Scale Mixture-of-Experts
arXiv:2610.02241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures allow frontier language models to scale to trillions of parameters, but their deployment is constrained by massive memory footprint…
- arXiv cs.AIagentsRxnOptBench: Benchmarking LLMs for Reaction-Condition Optimization in Organic Methodology
arXiv:2610.02242v1 Announce Type: cross Abstract: Chemical reaction-condition optimization -- choosing the catalyst, ligand, solvent, reagent, temperature, time, and atmosphere that jointly maximize yield and stereoselec…
- arXiv cs.AIresearchToward Controlling Biology with Language:Offline Learning of Prompt-Conditioned Interventions for Cells, Organoids, and Biobots
arXiv:2610.02247v1 Announce Type: cross Abstract: Artificial intelligence increasingly serves as a natural-language interface to complex technical systems, letting people accomplish sophisticated tasks by describing what…
- arXiv cs.AIresearchCounterfactual Predictions in Scientific Emulators Without Controlled Experiments
arXiv:2610.02252v1 Announce Type: cross Abstract: Many scientific questions require reasoning about what was never observed: What if the conditions, interventions, or history had been different? Models can predict accura…
- arXiv cs.AIresearchOvercoming Challenges of Interpretive Structural Modeling with Large Language Models
arXiv:2610.02254v1 Announce Type: cross Abstract: Interpretive Structural Modeling (ISM) is a well-known process for multi-criteria decision making. The success of ISM over other methodologies is its ability to model cau…
- arXiv cs.AIresearchDiffusion-Based Synthetic Data Pretraining for Enhancing Activity Recognition
arXiv:2610.02292v1 Announce Type: cross Abstract: Human activity recognition (HAR) is increasingly important for healthcare, well-being, and daily monitoring ap- plications, for which detecting alimentary activities such…
- arXiv cs.AIresearchEditHero: A Benchmark for Long-Horizon Part-Level 3D Editing and Vibe Modeling
arXiv:2610.02298v1 Announce Type: cross Abstract: 3D editing methods are usually tested on a single edit, yet an asset is built through a long sequence of revisions, each of which must implement the requested change whil…
- arXiv cs.AIresearch$\Psi$-Resilience: Model-Free Feature Importance from 1D Topological Signals
arXiv:2610.02299v1 Announce Type: cross Abstract: We introduce $\Psi$-Resilience, a model-free feature importance method that derives explanations directly from the data itself via 1D topological signals. Our method cons…
- arXiv cs.AIagentsSimuVerity: Benchmarking Agents for Engineering-Grade Simulink Model Generation
arXiv:2610.02304v1 Announce Type: cross Abstract: Existing Simulink benchmarks mainly evaluate whether generated models compile, execute, or resemble a reference model. These criteria do not establish whether a model sat…
- arXiv cs.AIagentsDeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents
arXiv:2610.02320v1 Announce Type: cross Abstract: Computer-use agents need to reliably ground action targets in complex desktop scenes, where multiple applications, overlapping windows, and visually similar controls comp…
- arXiv cs.AIresearchSlow-Fast Multi-Teacher On-Policy Distillation for Capability Preservation
arXiv:2610.02324v1 Announce Type: cross Abstract: Foundation multimodal large language models are designed to support a broad spectrum of capabilities across diverse domains. Multi-teacher on-policy distillation (MOPD) p…
- arXiv cs.AIagentsMIRROR: Multipath Quorum Integrity for LLM Multi-Agent Communication
arXiv:2610.02349v1 Announce Type: cross Abstract: Inter-agent communication is central to Large Language Model Multi-Agent Systems (LLM-MAS), but it introduces an underexplored vulnerability: Agent-in-the-Middle (AiTM) a…
- arXiv cs.AIresearchLexicographic Multi-Objective On-Policy Distillation
arXiv:2610.02359v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards (RLVR) usually optimizes answer correctness, yet useful language-model behavior also requires high-quality reasoning and co…
- arXiv cs.AIresearchAutomating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCI
arXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand from natural-language…
- arXiv cs.AIresearchNetwork-in-the-Loop at Scale: GPU-Batched 5G Simulation for Massively Parallel Robot Learning
arXiv:2610.02370v1 Announce Type: cross Abstract: Massively parallel GPU simulators train multi-robot policies in thousands of environments, and many fleets use private Fifth-Generation (5G) networks, where each robot's…
- arXiv cs.AIresearchHop-Decayed Influence: New Vulnerabilities of Structural Auxiliary Indexing in GraphRAG Pipelines with LLM
arXiv:2610.02373v1 Announce Type: cross Abstract: GraphRAG pipelines construct auxiliary structures during offline indexing--semantic summaries, hierarchical edges, and pre-computed scores--that determine how retrieval i…
- arXiv cs.AIresearchEviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision
arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning to generate such re…
- arXiv cs.AIagentsCoco: An Agentic Copilot for the Hardware--Software Co-Design Lifecycle
arXiv:2610.02376v1 Announce Type: cross Abstract: Co-designing ML models and the accelerators that run them is an unusual reasoning task: architects must draw confident, high-stakes conclusions about systems that do not…
- arXiv cs.AIresearchThe Surprising Effectiveness of Shared Memory in Looped Transformers
arXiv:2610.02383v1 Announce Type: cross Abstract: Looped Transformers apply the same layers several times per token, adding compute to improve quality without more parameters. Each recursion, however, writes its own key-…
- arXiv cs.AIagentsInherit-MAS: Test-Time Evolution of Multi-Agent Systems through Workflow and Execution Inheritance
arXiv:2610.02396v1 Announce Type: cross Abstract: Multi-agent systems (MAS) built from large language models coordinate specialized agents to tackle complex tasks, but effective workflows are difficult to design in advan…
- arXiv cs.AIresearchEfficient Neural Field Learning via Adaptive Coverage and Focused Sampling
arXiv:2610.02410v1 Announce Type: cross Abstract: Implicit neural representations (INRs) provide a flexible framework for modeling high-dimensional continuous fields, but their training is often inefficient due to unifor…
- arXiv cs.AIresearchMitigating Private Data Leakage in LLMs with Whiteout
arXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible website and user inputs. A…
- arXiv cs.AIresearchGeometry-Aware Time Reparameterization for Flow-Map Distillation
arXiv:2610.02427v1 Announce Type: cross Abstract: Flow-map distillation enables one- and few-step generation by learning finite-time transitions of a pretrained generative ODE. We investigate whether changing the teacher…
- arXiv cs.AIresearchLearning Style, Forgetting Semantics: A Case Study of SFT and RFT on Classification Tasks
arXiv:2610.02437v1 Announce Type: cross Abstract: Why does supervised fine-tuning (SFT) lead to more forgetting than reinforcement fine-tuning (RFT), even when all teacher demonstrations are semantically correct? We stud…
- arXiv cs.AIresearchAre you Synthesizing or Recalling? Evaluating LLMs on Algorithmic Code Retrieval
arXiv:2610.02438v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance in code generation, where success depends on both recalling relevant algorithmic knowledge and reasoning…
- arXiv cs.AIresearchCounterexample Generation via Per-Theorem Symbolic Verifiers: When Imitation Hurts and Reinforcement Repairs
arXiv:2610.02444v1 Announce Type: cross Abstract: Large language models often solve a theorem forward yet fail to disprove a closely related false one: a falsification gap that supervised fine-tuning does not close and c…
- arXiv cs.AIresearchFinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms
arXiv:2610.02455v1 Announce Type: cross Abstract: Multi-party financial chatrooms are vital for sales-and-trading professionals, but their complexity makes manual recovery of missed trades infeasible: each Request for Qu…
- arXiv cs.AIagentsSideKernel: A Usable microVM Sandbox for AI Coding Agents on macOS
arXiv:2610.02456v1 Announce Type: cross Abstract: AI coding agents are untrusted system components, yet they require autonomy on the developer machines they run on. This contradiction is a security problem. Sandboxes pro…
- arXiv cs.AIagentsAPDMem: Agent-Controlled Progressive Disclosure for Query-Adaptive Long-Term Memory
arXiv:2610.02472v1 Announce Type: cross Abstract: Personalized LLM assistants must recover sparse evidence from long conversation histories across queries of varying complexity. We introduce APDMem (Agent-controlled Prog…
- arXiv cs.AIresearchFrom Retrieval to Typed Decisions: Calibrated System One Models from Biomedical Sentence Encoders
arXiv:2610.02486v1 Announce Type: cross Abstract: Typed decision models answer schema-constrained questions about a text in one forward pass and return probabilities meant to be thresholded. We ask whether biomedical sen…
- arXiv cs.AIresearchCompound AI System Reliability: A Failure Taxonomy and Resilience Pattern Catalog from 150 Production Incidents
arXiv:2610.02503v1 Announce Type: cross Abstract: Deploying compound AI systems reliably and safely requires understanding failure modes that emerge at component boundaries, not within individual models. Cascading errors…
- arXiv cs.AIresearchMulti-Fidelity Policy Gradients Stabilize Data-Scarce Reinforcement Learning
arXiv:2610.02505v1 Announce Type: cross Abstract: Policy gradient methods for on-policy reinforcement learning (RL) can become unstable when expensive, scarce target-domain data yield noisy gradient estimates. We address…
- arXiv cs.AIagentsFrom Fragments to Global Maps: Learning Vectorized Map Aggregation with Large Language Models
arXiv:2610.02513v1 Announce Type: cross Abstract: Large-scale vectorized HD maps provide structured road information that is essential for perception, localization, and planning in autonomous driving. Constructing such m…
- arXiv cs.AIresearchIGNITE Tokamak World Model Architecture
arXiv:2610.02515v1 Announce Type: cross Abstract: We introduce IGNITE, a generative world foundation model for fusion plasma behavior simulation trained in a self-supervised manner from over a decade of unlabeled experim…
- arXiv cs.AIresearchStudent-Guided Teacher Distillation for Efficient LLM Task Routing: Positioning Against Jev-Style System-1 Classifiers
arXiv:2610.02516v1 Announce Type: cross Abstract: Zero-shot classifiers are useful for routing user requests to specialized LLM tasks, but scoring every request against a large candidate set is expensive: a zero-shot NLI…
- arXiv cs.AIresearchInstance-Dependent Regret for CMDPs with Step-Wise Constraints
arXiv:2610.02520v1 Announce Type: cross Abstract: We study online learning in episodic tabular constrained Markov decision processes with step-wise safety constraints. In such a setting, the constraints induce a safe sub…
- arXiv cs.AIresearchCriticHack: Evaluating Visual Rewards Under Robot Policy Optimization
arXiv:2610.02527v1 Announce Type: cross Abstract: Learned visual reward models are increasingly used to optimize robot policies, yet a reward model can score an execution that acts on the wrong object as highly as one th…
- arXiv cs.AIresearchOut of Sync, Out of Sight: Phantom State Attacks against IIoT Intrusion Detection
arXiv:2610.02552v1 Announce Type: cross Abstract: Machine learning-based intrusion detection systems (IDS) are critical for securing Industrial Internet of Things (IIoT) environments. Most adversarial research against th…
- arXiv cs.AIagentsOpenGameEval: Benchmarking Agentic Programming and Exploration in a Stateful Game Engine
arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in reproducible, statef…
- arXiv cs.AIresearchDAGS: Disentangled Appearance-and-Geometry Steering of a Frozen Image DiT for Temporally Stabilized Generative Rendering
arXiv:2610.02567v1 Announce Type: cross Abstract: Diffusion transformers (DiTs) generate high-fidelity images from text and image conditions, but their outputs carry large variance and their faithfulness to a desired tar…
- arXiv cs.AIagentsPincer: Resource Authorization for Agents using a Digital Twin
arXiv:2610.02569v1 Announce Type: cross Abstract: Coding agents have become increasingly long-horizon, autonomous, reliant on general-purpose shell and maintain their own persistent memory for self-improvement. While the…
- arXiv cs.AIresearchImproving the Energy-Efficiency of the Code Generated by LLMs through Effective Prompting
arXiv:2610.02571v2 Announce Type: replace-cross Abstract: As AI-assisted programming becomes increasingly mainstream, the environmental impact of AI-generated software has emerged as an important consideration. This moti…