AI news archive.
10,660 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchStructure-aware Reinforcement Learning for Protein Directed Evolution
arXiv:2609.39048v1 Announce Type: cross Abstract: Protein optimization remains a longstanding goal in life sciences. Existing machine learning-assisted directed evolution (MLDE) methods primarily rely on sequence-only fe…
- arXiv cs.AIresearchStructure vs. Chain-of-Thought: Evaluating LLM Criteria Extraction for Depression Severity
arXiv:2609.39049v2 Announce Type: replace-cross Abstract: A large language model (LLM) can rate depression severity directly from a social media post, or mark which clinical criteria the post shows and let a simple rule…
- arXiv cs.AIresearchA 3GPP-Compliant Benchmark Dataset for RIS-Aided Beyond 5G Networks
arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (B5G) networks. Howev…
- arXiv cs.AIresearchBeyond Text: LLM-Based Dimensional Emotion Evaluation in Multimodal Dialogue
arXiv:2609.39072v1 Announce Type: cross Abstract: Emotion recognition in conversation has been widely studied, but applying Large Language Models (LLMs) to continuous dimensional emotion evaluation in multimodal dialogue…
- arXiv cs.AIresearchHO-FL: Hybrid-Order Federated Learning for Heterogeneous Edge Devices
arXiv:2609.39074v1 Announce Type: cross Abstract: Federated learning (FL) on memory-constrained edge devices faces a dilemma: first-order (FO) optimization (i.e., backpropagation) demands substantial memory, whereas zero…
- arXiv cs.AIresearchRAGScope: A Leakage-Controlled, Cost-Aware Evidence-Gating Protocol for RAG Hallucination Triage
arXiv:2609.39075v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems need inexpensive ways to route generated answers: accept low-risk outputs, review uncertain ones, and reserve strong verifier…
- arXiv cs.AIresearchAssociation profile conditioning in a set-temporal transformer for cross-session intracortical motor decoding
arXiv:2609.39080v1 Announce Type: cross Abstract: Intracortical motor decoders degrade across sessions because the set of recorded units changes and persisting units can alter how their firing relates to behavior. Most e…
- arXiv cs.AIresearchTrustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail
arXiv:2609.39086v1 Announce Type: cross Abstract: Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state. Recent work shows that LLMs can generate such healing code,…
- arXiv cs.AIresearchSCIC: Scope- and Codebook-Aware Instruction Conditioning for Speaker-Adapted Expressive TTS
arXiv:2609.39088v1 Announce Type: cross Abstract: Long-form live-streaming TTS requires context-dependent prosody and paragraph-level coherence. However, many existing instruction-based TTS systems use global or uniform…
- arXiv cs.AIresearchA Generalisation Signal Need Not Be a Model-Selection Signal
arXiv:2609.39099v2 Announce Type: replace-cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When validation no…
- arXiv cs.AIresearchT-Router: Learning Thalamic Routing for Reasoning with Parameter-Efficient Reinforcement Learning
arXiv:2609.39109v1 Announce Type: cross Abstract: Parameter-efficient reinforcement learning aims to improve reasoning with a compact trainable interface to a pretrained model. We introduce the Thalamic Router (T-Router)…
- arXiv cs.AIresearchBlackout vs. Freeze: Analyzing Physical Failure Modes of VLAs under Camera Faults
arXiv:2609.39145v1 Announce Type: cross Abstract: Unreliable visual inputs can harm task performance and cause potential physical safety risks for vision-language-action (VLA) models. We analyze how $\pi 0.5$ and GR00T m…
- arXiv cs.AIresearchMEND: Label-Free Detection, Localisation, and Correction of Latent Hallucination in World Models
arXiv:2609.39182v1 Announce Type: cross Abstract: World Models are appearing as the next major frontier in computer vision. However, their robustness is currently largely unexplored. We identify the phenomenon of halluci…
- arXiv cs.AIresearchUniAE-MoE: A Unified Audio Encoder via Mixture of Experts
arXiv:2609.39199v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) rely on effective audio encoders for multi-task performance. We introduce UniAE-MoE, a unified audio encoder designed to model…
- arXiv cs.AIresearchIn a Streaming World, Should You Stand Still? A Comprehensive Benchmark of Anomaly Detection in Streams
arXiv:2609.39215v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) is increasingly deployed in streaming settings, where data arrive sequentially and may exhibit non-stationarity. As a result, several…
- arXiv cs.AIresearchEmergent Multi-View Geometry Through Self-Distillation
arXiv:2609.39227v1 Announce Type: cross Abstract: Over a century ago, Henri Poincar\'e argued that a motionless observer cannot acquire the notion of space. Yet, most visual representation learning methods operate on ind…
- arXiv cs.AIresearchRAIM: Robust Aggregation of Inexpensive Models for Hallucination Detection
arXiv:2609.39229v1 Announce Type: cross Abstract: Automatic evaluation of faithfulness increasingly relies on a large language model acting as a judge, yet the most reliable judges are proprietary frontier models, costly…
- arXiv cs.AIresearchWhat Streaming Anomaly Detection Finds (and Misses) in Industrial Time Series
arXiv:2609.39232v1 Announce Type: cross Abstract: EDF relies on continuous monitoring of its power plants to detect anomalies as soon as they occur. Given the absence of a universally optimal streaming method in unsuperv…
- arXiv cs.AIresearchTrust the Critic More
arXiv:2609.39247v2 Announce Type: replace-cross Abstract: Standard language model RL algorithms credit every token of a long rollout with the same advantage determined by the terminal reward. Actor-critic methods can pro…
- arXiv cs.AIresearchFrom Benchmarks to Production: Transferring Time Series Anomaly Detection Methods for Electricity Production Monitoring
arXiv:2609.39257v1 Announce Type: cross Abstract: Accurate forecasting of electricity production is essential for maintaining the operational efficiency and strategic planning of energy utilities. In industrial settings,…
- arXiv cs.AIresearchA Time-Aware Bag-of-Receptive-Fields for Interpretable Irregular Time Series Classification
arXiv:2609.39268v1 Announce Type: cross Abstract: Irregular time series, characterized by non-uniform sampling intervals, missing observations, and variable lengths, are ubiquitous in healthcare, mobility, and environmen…
- arXiv cs.AIresearchFaithful Dual-constrained Erasure for Robust LLM Safety Alignment
arXiv:2609.39279v1 Announce Type: cross Abstract: Machine unlearning has emerged as a crucial mechanism for removing hazardous knowledge and enforcing safety alignment in Large Language Models (LLMs). However, recent stu…
- arXiv cs.AIresearchEngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses
arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning, complex state manag…
- arXiv cs.AIresearchGRPO Training Dynamics for Small Language Models
arXiv:2609.39321v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has emerged as a memory-efficient reinforcement fine-tuning (RFT) technique for reasoning-intensive tasks. How- ever, GRPO train…
- arXiv cs.AIresearchHiWE: Hierarchical World Knowledge Model with Visual Keypoint Enhancement for Zero-Shot 3D Path Planning
arXiv:2609.39323v1 Announce Type: cross Abstract: Robot demonstration generation requires a system to identify where an interaction should occur, plan a feasible motion, and execute the required contact. HiWE connects th…
- arXiv cs.AIresearchWinoTS: Wavelet-based Self-Distillation for Time Series Models
arXiv:2609.39337v1 Announce Type: cross Abstract: Self-supervised pre-training of time series models is currently dominated by next-token prediction and reconstruction objectives. In continuous-valued domains, these para…
- arXiv cs.AIresearchWho Said What, and Will It Be Remembered? Evaluating Persistent Speaker Attribution Across Meetings
arXiv:2609.39344v1 Announce Type: cross Abstract: Speech transcripts used as long-term memory must preserve both words and stable speaker identities. Existing meeting-transcription metrics either ignore speakers or remap…
- arXiv cs.AIresearchWorking Around the Compute Ceiling: Byte-Exact Memory in Galahad Makes LLM Reading a One-Time Cost LLM Reading a One-Time Cost
arXiv:2609.39358v1 Announce Type: cross Abstract: A transformer language model performs a bounded amount of computation per token, and recent work by Vishal Sikka, former CEO of Infosys, argues that this bound limits whi…
- arXiv cs.AIresearchRethinking Multi-Image Re-Representation in Multi-Image Understanding
arXiv:2609.39363v1 Announce Type: cross Abstract: Multi-image understanding requires MLLMs not only to recognise the content of individual images, but also to organise visual evidence distributed across them. We study th…
- arXiv cs.AIresearchReady2Blend: From Natural-Language Instructions to Composable Alignment Prompts
arXiv:2609.39365v2 Announce Type: replace-cross Abstract: Continual alignment requires LLMs to adapt to new requirements without forgetting previously acquired behaviors. Natural-language instructions are flexible and co…
- arXiv cs.AIresearchWavelet Flow Matching for Time Series
arXiv:2609.39374v2 Announce Type: replace-cross Abstract: Synthetic time series are increasingly used for data augmentation, privacy-preserving data sharing, and downstream model development, yet faithfully reproducing b…
- arXiv cs.AIresearchFrom Search to Signal: Online Post-Training in Automatic Heuristic Design
arXiv:2609.39383v1 Announce Type: cross Abstract: Large language model (LLM)-based automatic heuristic design (AHD) iteratively proposes and refines heuristics, pairing design rationales with executable code. Task-specif…
- arXiv cs.AIresearchTTLab at Daleel 2026: STAR-Ar, Sequence Tagging for Argument Recognition in Arabic
arXiv:2609.39385v1 Announce Type: cross Abstract: Argument Mining (AM) is a critical NLP task that remains significantly under-resourced in Arabic. This paper presents $\testtt{STAR-Ar}$, a BERT-BiLSTM-CRF architecture f…
- arXiv cs.AIresearchTowards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification
arXiv:2609.39429v1 Announce Type: cross Abstract: Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis. In this work, we evaluate UQ in a multi-task Deep Learning…
- arXiv cs.AIresearchCAST: Causal Advantage-Structured Training with Spatially Grounded Compositional Rewards for Diffusion Models
arXiv:2609.39441v1 Announce Type: cross Abstract: Online reinforcement learning has been extended to flow matching for diffusion model (DM) image generation. However, this paradigm faces three limitations: (1) Window sel…
- arXiv cs.AIresearchFrom Speech to Editable Concepts: Probing Emotion Recognition with Concept Bottleneck Models
arXiv:2609.39453v1 Announce Type: cross Abstract: Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent approaches combine multi…
- arXiv cs.AIresearchCAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series
arXiv:2609.39484v1 Announce Type: cross Abstract: Longitudinal clinical cohorts are multimodal, irregularly sampled and pervasively incomplete: in ADNI, positron emission tomography and cerebrospinal fluid assays are abs…
- arXiv cs.AIresearchOmniReasoning: Pushing the Limits of Audio-Visual Joint Reasoning
arXiv:2609.39490v2 Announce Type: replace-cross Abstract: Recent advances have enabled unified omni-modal models in understanding audio, vision, and language. However, existing benchmarks, training data, and learning met…
- arXiv cs.AIresearchPartiCam: Camera Controlled Video Generation with Reward Guidance
arXiv:2609.39504v1 Announce Type: cross Abstract: We present PartiCam, a training-free Particle filtering rooted method for improved Camera controlled video generation. Generating videos that follow a precisely specified…
- arXiv cs.AIresearchA Reusable Semantic Web Framework for Evidence-Grounded Fundamental Rights Impact Assessments under the EU AI Act
arXiv:2609.39537v1 Announce Type: cross Abstract: The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the evidence needed for…
- arXiv cs.AIresearchLearning Normal Diffusion Dynamics for Backdoor Defense in Text-to-Image Models
arXiv:2609.39548v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the secure deployment of text-to-image (T2I) diffusion models. Existing defenses typically detect backdoors from specific abnorm…
- arXiv cs.AIresearchCandidate Retention for Abductive Learning
arXiv:2609.39561v1 Announce Type: cross Abstract: Abductive learning combines neural perception with symbolic reasoning, using explanations generated by abduction to supervise the perception model. Multiple valid explana…
- arXiv cs.AIresearchSelf-Spec Verifiable Code Generation
arXiv:2609.39568v1 Announce Type: cross Abstract: Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable guarantees. Recently,…
- arXiv cs.AIresearchSteering Fields: Adaptive Vector Fields for Safe Image Generation and Beyond
arXiv:2609.39573v1 Announce Type: cross Abstract: As state-of-the-art text-to-image flow models achieve near-photorealistic quality, controlling their outputs, e.g., suppressing harmful content while promoting benign alt…
- arXiv cs.AIresearchECHO-G: Embodied Co-speech Humanoid mOtion Generation
arXiv:2609.39575v1 Announce Type: cross Abstract: Generating full-body co-speech motion for humanoid robots requires coordinating speech prosody, linguistic content, and embodiment-specific motion. To this end, we presen…
- arXiv cs.AIresearchRobust Transfer Learning for Paper ECG Recognition
arXiv:2609.39581v1 Announce Type: cross Abstract: Paper ECG recognition is challenging because real-world ECG images vary in layout, physical artifacts, and label availability. We introduce RobECG-CL, a rank-aware contra…
- arXiv cs.AIresearchText-to-3D Policy: Fine-Grained Language-Behavior Alignment for Unseen Specification Generalization
arXiv:2609.39599v1 Announce Type: cross Abstract: 3D visuomotor policies provide a strong foundation for spatially precise manipulation, yet current text-to-3D policies struggle to follow unseen fine-grained behavioral s…
- arXiv cs.AIresearchGroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed
arXiv:2609.39600v2 Announce Type: replace-cross Abstract: Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal order on output tokens. We view grounding…
- arXiv cs.AIresearchGroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
arXiv:2609.39601v2 Announce Type: replace-cross Abstract: Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fast enough fo…
- arXiv cs.AIresearchD-Scope: Decomposing and Steering Diffusion Transformers with Sparse Autoencoders
arXiv:2609.39625v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) reveal visual structure in diffusion transformers (DiTs), but interpreting a feature does not establish whether it can be used to control gener…