AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSpikeLite: Lightweight Spiking Neural Networks for Time-Series Forecasting
arXiv:2609.35097v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer an energy-efficient paradigm for time-series forecasting through spike-driven computation. However, recent SNN forecasters often purs…
- arXiv cs.AIresearchA mechanistic study of language model introspection
arXiv:2609.35108v1 Announce Type: cross Abstract: Large language models (LLMs) can sometimes report perturbations to their internal activations---even when the input provides no evidence that an intervention occurred. Ho…
- arXiv cs.AIresearchCTP-FL: Common-Trajectory Gradient Prediction for Federated Learning
arXiv:2609.35130v1 Announce Type: cross Abstract: Communication-efficient federated optimization commonly spends several gradient evaluations between server updates. Existing local-update methods use this computation to…
- arXiv cs.AIagentsTimeline-Bench: Evaluating Agents on Realistic Video-Editing Tasks, from Raw Footage to Final Cut
arXiv:2609.35143v1 Announce Type: cross Abstract: AI agents increasingly carry out long-horizon professional work, but their evaluations rarely require a finished creative deliverable. To this end, we introduce Timeline-…
- arXiv cs.AIresearchLearning to Re-Draft: A Variational Stackelberg Game for Discrete Diffusion
arXiv:2609.35166v1 Announce Type: cross Abstract: Discrete diffusion models offer the ability to re-draft, revisiting and correcting earlier tokens throughout generation. This capability depends on the forward corruption…
- arXiv cs.AIresearchQAM: Quadratic-Accurate Checkpoint Merging via Sequential Consistency
arXiv:2609.35168v1 Announce Type: cross Abstract: Saved checkpoints record states along a training trajectory, but generally do not determine the updates at states that would be visited under a different schedule. We stu…
- arXiv cs.AIagentsResearch-Native by Construction: Minimal Nodes, Re-verifiable Workflows, and Compounding Memory for Long-Horizon Scientific Agents
arXiv:2609.35182v1 Announce Type: cross Abstract: We describe AfS (Agent for Science), a platform built for long-horizon scientific work, where a project runs for tens of hours across dozens of agent runs with a human pr…
- arXiv cs.AIresearchCarveMix-RC: Addressing Rare-Class Imbalance Through Lesion-Aware Synthetic Augmentation for Brain Metastasis Segmentation
arXiv:2609.35195v1 Announce Type: cross Abstract: Accurate segmentation of post-treatment brain metastases is essential for treatment planning, longitudinal disease monitoring, and quantitative assessment of therapeutic…
- arXiv cs.AIresearchGAC-PINN: Geometry-Adaptive and Constraint-Enhanced Physics-Informed Neural Networks
arXiv:2609.35196v1 Announce Type: cross Abstract: For systems with steep gradients, sharp interfaces, or severe spatio-temporal coupling, Physics-informed neural networks (PINNs) suffer from spectral bias, geometric infl…
- arXiv cs.AIresearchAlignment Games: A Framework for Conceptual Repair in Human-AI Collaboration
arXiv:2609.35197v1 Announce Type: cross Abstract: The meaning of a concept in use is shaped by the situation, task, goals, and prior knowledge. For example, a request to make a poster "visually appealing for a five-year-…
- arXiv cs.AIresearchReCAT: Remember, Count, and Time: Structured Recurrent Memory for Robot Manipulation
arXiv:2609.35200v1 Announce Type: cross Abstract: Memory-dependent manipulation requires robots to make decisions using information that is no longer available to their current sensors, such as recalling an earlier visua…
- arXiv cs.AIresearchFrom Normative Frameworks to Alignment Data: Constructing and Evaluating SFT and Preference Data
arXiv:2609.35201v1 Announce Type: cross Abstract: Aligning language models with a specified normative framework requires translating abstract principles into concrete examples and preference signals from which models can…
- arXiv cs.AIresearchGenerative AI-Based Data Augmentation for Oral Lesion Classification: The PhotoMOCI Dataset and Benchmark
arXiv:2609.35226v1 Announce Type: cross Abstract: Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of robust deep learnin…
- arXiv cs.AIresearchToken-Disentangled Latent Test-Time Scaling for Vision-Language Reasoning
arXiv:2609.35228v1 Announce Type: cross Abstract: Latent test-time scaling improves reasoning by refining hidden states during inference, but existing methods typically apply a single scalar reward to all editable latent…
- arXiv cs.AIresearchSpatial Grafting: Grounding 3D Features for Flow-Matching Robot Policies
arXiv:2609.35249v1 Announce Type: cross Abstract: Pretrained robot manipulation policies such as vision-language-action models (VLAs) or world-action models (WAMs) leave interaction-relevant metric geometry implicit. Rec…
- arXiv cs.AIresearchWavePP: High-Throughput Pipeline Parallel LLM Prefill under Prefix Reuse
arXiv:2609.35263v1 Announce Type: cross Abstract: Pipeline parallelism can improve prefill throughput by processing multiple request chunks concurrently across different stages of the model. However, keeping the pipeline…
- arXiv cs.AIresearcheval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models
arXiv:2609.35269v1 Announce Type: cross Abstract: The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods are assessed under het…
- arXiv cs.AIresearchMulti-Attractor GNNs: Set-Valued Expressivity Beyond Unique Equilibria
arXiv:2609.35274v1 Announce Type: cross Abstract: Recurrent and equilibrium graph neural networks (GNNs) often enforce a unique fixed point or use one training target per graph. Yet many combinatorial and scientific prob…
- arXiv cs.AIagentsTeacher-Student Gaps Are Not Enough: Outcome-Guided On-Policy Distillation for Multi-Turn Autonomous Agents
arXiv:2609.35319v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student on its own trajectories with dense teacher supervision. Recent work on OPD for multi-turn autonomous agents often treats lar…
- arXiv cs.AIresearchReverse Sequential Proportional Approval Voting Rule: Proportionality and Approximation Guarantees
arXiv:2609.35331v1 Announce Type: cross Abstract: We study the Reverse Sequential Proportional Approval Voting Rule (RevSeqPAV) in approval-based committee elections. Despite its historical prominence and practical use,…
- arXiv cs.AIresearchLarge Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation
arXiv:2609.35335v1 Announce Type: cross Abstract: Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We investigate whether lar…
- arXiv cs.AIresearchFrom Data to Program: Fast & Direct Generative Program Inference from Empirical Data
arXiv:2609.35348v1 Announce Type: cross Abstract: Estimating probability densities from a finite set of samples typically requires dataset-specific model fitting. We introduce PRODiGI, a pretrained data-to-program model…
- arXiv cs.AIagentsDo Coding Agents Reuse Existing Code or Reinvent the Wheel?
arXiv:2609.35357v1 Announce Type: cross Abstract: Coding agents are increasingly deployed for iterative development on real repositories, yet existing evaluation barely answers a basic question: \emph{do coding agents re…
- arXiv cs.AIresearchd-OPD: Future-Aware On-Policy Distillation for Block Diffusion Language Models
arXiv:2609.35362v1 Announce Type: cross Abstract: Large language models (LLMs) typically generate text autoregressively (AR), predicting one token at a time. Block diffusion language models (dLLMs) instead generate block…
- arXiv cs.AIresearchDo Temporal Link Predictors Need Learned Memory? A Smoothed-Count Baseline with a Handful of Parameters
arXiv:2609.35364v1 Announce Type: cross Abstract: Many temporal link predictors summarize past interactions through learned node representations. We examine whether simple counts of recurring interaction patterns can pro…
- arXiv cs.AIagentsPlanarian: Managing Agent State with Statepoints
arXiv:2609.35366v1 Announce Type: cross Abstract: LLM agents solve complex tasks by iteratively changing files, invoking local tools, and interacting with remote services, which modifies state across their local environm…
- arXiv cs.AIresearchFrom Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations
arXiv:2609.35375v1 Announce Type: cross Abstract: Scaling up robotic manipulation is primarily bottlenecked by the scarcity of real-world robot data. While recent approaches leverage human video demonstrations to mitigat…
- arXiv cs.AIagentsMultilinguality in Hybrid Attention LLMs
arXiv:2609.35378v1 Announce Type: cross Abstract: In response to the growing demand for long sequences in agentic and reasoning use cases, many state-of-the-art LLMs combine multiple variants of attention to mitigate the…
- arXiv cs.AIagentsMCP Error Messages Written for Developers Hurt the Most Capable Agents Most
arXiv:2609.35381v2 Announce Type: replace-cross Abstract: Many Model Context Protocol (MCP) servers wrap web APIs built for human developers, and their error messages tell the reader to run a command, edit a configuratio…
- arXiv cs.AIresearchThe Hidden Ratio in Adam: Stable Structure, Compression, and Sign Dynamics
arXiv:2609.35392v1 Announce Type: cross Abstract: Adam is the default optimizer for training modern deep neural networks, yet its adaptive behavior remains poorly understood due to the complex interaction between its fir…
- arXiv cs.AIagents"Nothing to See Here'': Unintended Disclosure through Revision Traces of LLM Deliverables
arXiv:2609.35408v1 Announce Type: cross Abstract: Large language model (LLM) assistants increasingly help users draft content for third-party recipients. During private drafting, the user or the model may introduce an it…
- arXiv cs.AIresearchAwarenessBench: Assessing Cognitive Capabilities of Language Models
arXiv:2609.35409v1 Announce Type: cross Abstract: As language models (LMs) exhibit increasingly consciousness-like behaviors, evaluating their cognitive abilities becomes essential. We introduce AwarenessBench, the first…
- arXiv cs.AIresearchSpectral Super-Resolution using Spatial-Spectral Residual Operator Networks
arXiv:2609.35410v1 Announce Type: cross Abstract: Spectral super-resolution of multispectral satellite images can enable high temporal- and spatial-resolution hyperspectral satellite imagery at a modest cost, significant…
- arXiv cs.AIresearchGLAD: Global-Local Adaptive Detector for Robust Speech Deepfake Detection
arXiv:2609.35411v1 Announce Type: cross Abstract: Recent advances in AI-based speech synthesis have enabled highly realistic speech, increasing the importance of speech deepfake detection (SDD) in preventing misuse. Whil…
- arXiv cs.AIresearchSemantic Prefix Oracles for LLM Decoding: Contracts and Differential Validation
arXiv:2609.35425v1 Announce Type: cross Abstract: Constrained decoding can enforce regular or context-free output formats, but many program-generation failures are semantic: scope, typing, and declaration effects depend…
- arXiv cs.AIresearchFrontier Learning: Training LLM Reasoners at the Edge of Capability
arXiv:2609.35426v1 Announce Type: cross Abstract: Reinforcement Learning-based post-training of Large Language Models (LLM) has been successfully applied to improve their reasoning capabilities. Existing pipelines primar…
- arXiv cs.AIresearchReSPO: Reshaped Sequence Policy Optimization for Gradient Starvation in Off-Policy Learning
arXiv:2609.35433v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards (RLVR) frequently reuses rollouts across multiple policy updates, increasing the mismatch between the current policy and th…
- arXiv cs.AIresearchRiccati State Space Models: Non-iterative Parallelization for Nonlinear Sequence Modeling
arXiv:2609.35441v1 Announce Type: cross Abstract: State space models (SSMs) achieve efficient sequence processing because their affine state updates are closed under composition and can therefore be evaluated with an ass…
- arXiv cs.AIresearchCLIMB: A Clinical Multimorbidity Benchmark for Diagnosing Co-occurring Conditions through Multiturn Conversations
arXiv:2609.35462v1 Announce Type: cross Abstract: Patients often have several co-occurring clinical conditions, and the findings needed to identify and disambiguate them emerge over the course of a consultation. Evaluati…
- arXiv cs.AIresearchRethinking Causal Action Tokenization with Conditional Annealing in Flow Matching
arXiv:2609.35469v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action (VLA) models offer a scalable path to robot learning, yet existing action tokenizers treat tokenization as a compression problem, pr…
- arXiv cs.AIresearchSpontaneous Context Restoration: How Language Models Recover from Corrupted Inputs
arXiv:2609.35475v1 Announce Type: cross Abstract: Language models sometimes produce correct outputs even when their inputs are corrupted by deletion, replacement, or misspelling. We study the internal processes accompany…
- arXiv cs.AIresearchAnalog Computing revisited: A fully analog and minimalistic Damage Detector for Ultrasonic Testing enabling Material-Integrated Structural Health Monitoring
arXiv:2609.35478v1 Announce Type: cross Abstract: Ultrasonic Testing (UT) is commonly used to detect damage in structures, e.g., metal plates. A sensor acquires Ultrasonic waves, e.g., by using PZT transducers. The time-…
- arXiv cs.AIresearchFrom Scores to Samples: Elastic Forcing for Autoregressive Video Generation
arXiv:2609.35491v3 Announce Type: replace-cross Abstract: Few-step autoregressive video generation commonly relies on Distribution Matching Distillation (DMD), requiring a bidirectional diffusion teacher and an online fa…
- arXiv cs.AIresearchSolveEdit: Benchmarking Visual Problem Solving in Generative Models
arXiv:2609.35504v1 Announce Type: cross Abstract: Machine intelligence is often evaluated through abstract reasoning problems, yet many real-world problems are visual, such as arranging objects, repairing layouts, or tra…
- arXiv cs.AIresearchImproving Generative Model Self-Training with Geometrically Modified Outputs
arXiv:2609.35512v1 Announce Type: cross Abstract: Self-training generative models - the continued improvement of a model using its own outputs - is becoming increasingly important as high-quality training data becomes sc…
- arXiv cs.AIresearchBeyond Token Scale: Chunk-Level Sparse Autoencoders for Reliable Semantic Feature Discovery
arXiv:2609.35521v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) expose features that help us understand and steer language models, but faithful reconstruction does not guarantee informative concepts. Token-l…
- arXiv cs.AIresearchLet the Neurons Die: Exploiting ReLU-Induced Model Degradation
arXiv:2609.35528v1 Announce Type: cross Abstract: Rectified linear unit (ReLU) networks can suffer from dying neurons, where units with persistently negative pre-activations produce zero outputs, blocking gradients throu…
- arXiv cs.AIagentsAutoRef: Harness Optimization for Agentic Multi-Reference Image Generation
arXiv:2609.35530v1 Announce Type: cross Abstract: Recent image generation models can take multiple reference images as input and combine them into a new image. However, multi-reference image generation remains challengin…
- arXiv cs.AIresearchLess Sycophancy, Stronger Refusal? Lessons for AI Safety from Mechanistic Interpretability
arXiv:2609.35544v1 Announce Type: cross Abstract: Reliable refusal of harmful requests is essential to the safe deployment of language models. Because excessive eagerness to please users may undermine existing refusal ca…
- arXiv cs.AIresearchGraph World Models for Constrained Epidemic Policy Planning
arXiv:2609.35545v2 Announce Type: replace-cross Abstract: Epidemic policy planning often requires coordination between geographical regions, taking into account mobility-driven spillovers and how to make use of limited r…