AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchCognifying Education: Mapping AI's transformative role in emotional, creative, and collaborative learning
arXiv:2509.25266v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is rapidly reshaping educational practice, challenging long held assumptions about teaching and learning. This article integrates con…
- arXiv cs.AIresearchFrequency-Aware Model Parameter Explorer: A new attribution method for improving explainability
arXiv:2510.03245v3 Announce Type: replace-cross Abstract: State-of-the-art attribution methods such as AttEXplore rely on adversarial sample generation that applies an all-pass filter across the frequency spectrum: they…
- arXiv cs.AIresearchRethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
arXiv:2510.05023v2 Announce Type: replace-cross Abstract: Langevin-based Thompson Sampling (TS) methods for multi-armed bandits use likelihood gradients to approximate posterior samples when exact sampling is intractable…
- arXiv cs.AIresearchBatch Bayesian Active Learning with Partial Batch Label Sampling
arXiv:2510.09877v4 Announce Type: replace-cross Abstract: Over the past couple of decades, many active learning acquisition functions have been proposed, leaving practitioners with an unclear choice of which to use. Baye…
- arXiv cs.AIresearchA Function-Centric Perspective on Flat and Sharp Minima
arXiv:2510.12451v3 Announce Type: replace-cross Abstract: Flat minima are strongly associated with improved generalisation in deep neural networks. However, this connection has proven nuanced in recent studies, with both…
- arXiv cs.AIresearchSoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses
arXiv:2510.15476v5 Announce Type: replace-cross Abstract: Prompt-security claims for large language models (LLMs) are often compared as properties of individual attacks or defenses, although measured harmfulness depends…
- arXiv cs.AIresearchIterative Critique-Refine Framework for Enhancing LLM Personalization
arXiv:2510.24469v2 Announce Type: replace-cross Abstract: Personalized text generation requires models not only to produce coherent text but also to align with a target user's style, tone, and topical focus. Existing ret…
- arXiv cs.AIresearchTraining LLMs Beyond Next Token Prediction - Filling the Mutual Information Gap
arXiv:2511.00198v2 Announce Type: replace-cross Abstract: Autoregressive language models are usually trained with next-token prediction under a fixed left-to-right target order. This paper studies target-token organizati…
- arXiv cs.AIresearchEnergy-Efficient Deep Learning Without Backpropagation: A Rigorous Hardware-Validated Benchmarking Study of Forward-Only Algorithms
arXiv:2511.01061v2 Announce Type: replace-cross Abstract: Backpropagation (BP) powers modern deep learning, but it must hold every activation in memory until a global backward sweep consumes it, and that sweep locks each…
- arXiv cs.AIresearchExploring the Underwater World Segmentation without Extra Training
arXiv:2511.07923v3 Announce Type: replace-cross Abstract: Accurate segmentation of marine organisms is vital for biodiversity monitoring and ecological assessment, yet existing datasets and models remain largely limited…
- arXiv cs.AIresearchNaga: Vedic Encoding for Deep State Space Models
arXiv:2511.13510v2 Announce Type: replace-cross Abstract: This paper presents Naga, a deep State Space Model (SSM) encoding approach inspired by structural concepts from Vedic mathematics. The proposed method introduces…
- arXiv cs.AIresearchUnSAMv2: Self-Supervised Learning Enables Segment Anything at Any Granularity
arXiv:2511.13714v2 Announce Type: replace-cross Abstract: The Segment Anything Model (SAM) family has become a widely adopted vision foundation model, but its ability to control segmentation granularity remains limited.…
- arXiv cs.AIresearchNeural Evidence and Behavioural Welfare Economics: When Can Neuroeconomics Inform Policy?
arXiv:2511.19548v2 Announce Type: replace-cross Abstract: Neuroeconomics appears to offer welfare economics an evidential supplement, since neural data may help distinguish choices that express genuine preferences from c…
- arXiv cs.AIresearchExplainable Visual Anomaly Detection via Concept Bottleneck Models
arXiv:2511.20088v3 Announce Type: replace-cross Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanations by highli…
- arXiv cs.AIresearchSemantics as a Shield: Label Disguise Defense (LDD) against Prompt Injection in LLM Sentiment Classification
arXiv:2511.21752v3 Announce Type: replace-cross Abstract: Prompt injection can cause large language models (LLMs) to deviate from their intended tasks by following instructions embedded in untrusted input. We investigate…
- arXiv cs.AIresearchMeasuring all the noises of LLM Evals
arXiv:2512.21326v3 Announce Type: replace-cross Abstract: Applying well-established statistical methods effectively to LLM evals requires consideration of model correlations and prediction noises. Leading evals often ign…
- arXiv cs.AIresearchPhyAVBench: A Challenging Audio Physics-Sensitivity Benchmark for Physically Grounded Text-to-Audio-Video Generation
arXiv:2512.23994v5 Announce Type: replace-cross Abstract: Text-to-audio-video (T2AV) generation is central to applications such as filmmaking and world modeling. However, current models often fail to produce physically p…
- arXiv cs.AIresearchMechanistic Knobs in LLMs: Retrieving and Steering High-Order Semantic Features via Sparse Autoencoders
arXiv:2601.02978v3 Announce Type: replace-cross Abstract: Recent work in Mechanistic Interpretability (MI) has enabled the identification and intervention of internal features in Large Language Models (LLMs). However, a…
- arXiv cs.AIresearchHERO: Hierarchical Evidential Reasoning Optimization for Radiology Report Generation via Reason-then-Summarize
arXiv:2601.03321v5 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have substantially advanced Radiology Report Generation (RRG), yet aligning them through reinforcement learning (RL) rema…
- arXiv cs.AIresearchECLIPTICA -- A Framework for Switchable LLM Alignment via CITA - Contrastive Instruction-Tuned Alignment
arXiv:2601.06157v2 Announce Type: replace-cross Abstract: Alignment in large language models (LLMs) is still largely static: after training, the policy is frozen. DPO, GRPO methods typically imprint one behavior into the…
- arXiv cs.AIresearchGeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models
arXiv:2601.07632v5 Announce Type: replace-cross Abstract: Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-language reason…
- arXiv cs.AIresearchHiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids
arXiv:2601.07718v2 Announce Type: replace-cross Abstract: Achieving robust humanoid locomotion in complex, unstructured environments requires transitioning from reactive proprioception to proactive perception. However, i…
- arXiv cs.AIresearchRepresentational Similarity Alignment of Figurative Language in Humans and Large Language Models
arXiv:2601.09041v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce judgments similar to those of humans, but their interpretation of figurative language remains unclear. We compared huma…
- arXiv cs.AIresearchArchitecture Before the Formula: Training-Dependent Computational Semantics in Transformers
arXiv:2601.11618v4 Announce Type: replace-cross Abstract: An operation's input-output function does not, by itself, determine its computational role within a represented process. That role also depends on the processes p…
- arXiv cs.AIresearchLess is More: Label-Guided Efficient Summarization of Procedural and Instructional Videos
arXiv:2601.12243v3 Announce Type: replace-cross Abstract: Video summarization transforms long videos into concise representations that are easier to document and analyze, especially in high-stakes domains such as surgica…
- arXiv cs.AIresearchNeuroVLA: A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control
arXiv:2601.14628v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models inherit powerful semantic representations from large language models, but carrying over their design priorities can leave the…
- arXiv cs.AIresearchWhere is the multimodal goal post? On the Ability of Foundation Models to Recognize Highlights in Videos
arXiv:2601.16333v3 Announce Type: replace-cross Abstract: Foundation models are used for many real-world applications involving language understanding and generation from temporally-ordered multimodal events. In this wor…
- arXiv cs.AIresearchRetell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story Retelling
arXiv:2601.17226v3 Announce Type: replace-cross Abstract: Counterfactual storytelling exposes LLM shortcomings in causal reasoning, where few-shot prompting and SFT fail to produce logical and rational narratives. This c…
- arXiv cs.AIresearchUni-RS: A Spatially Faithful Unified Understanding and Generation Model for Remote Sensing
arXiv:2601.17673v2 Announce Type: replace-cross Abstract: Unified remote sensing multimodal models exhibit a pronounced spatial reversal curse: Although they can accurately recognize and describe object locations in imag…
- arXiv cs.AIresearchPixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models
arXiv:2601.19060v2 Announce Type: replace-cross Abstract: Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on modular pipelines th…
- arXiv cs.AIresearchThe pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis
arXiv:2601.19618v3 Announce Type: replace-cross Abstract: Differential privacy limits how much each training image can influence a medical imaging model but lowers its diagnostic accuracy. Pretrained weights reduce this…
- arXiv cs.AIresearchVERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning
arXiv:2601.20055v3 Announce Type: replace-cross Abstract: Despite the syntactic fluency of Large Language Models (LLMs), ensuring their logical correctness in high-stakes domains remains a fundamental challenge. We prese…
- arXiv cs.AIresearchScalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening
arXiv:2601.21590v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) post-training is a dominant approach for improving the reasoning performance of large language models (LLMs), yet growing evidence sug…
- arXiv cs.AIresearchOpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation
arXiv:2601.22725v5 Announce Type: replace-cross Abstract: Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remains a persistent…
- arXiv cs.AIresearchFrom Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs
arXiv:2602.00628v3 Announce Type: replace-cross Abstract: We investigate the extent to which an LLM's hidden-state geometry can be recovered from its behavior in psycholinguistic experiments. Across eight instruction-tun…
- arXiv cs.AIresearchDCD: Decomposition-based Causal Discovery from Autocorrelated and Non-Stationary Temporal Data
arXiv:2602.01433v3 Announce Type: replace-cross Abstract: Multivariate time series in domains such as finance, climate science, and healthcare often exhibit long-term trends, seasonal patterns, and short-term fluctuation…
- arXiv cs.AIresearchTTT-Parkour: Rapid Test-Time Training for Perceptive Robot Parkour
arXiv:2602.02331v2 Announce Type: replace-cross Abstract: Achieving highly dynamic parkour with humanoid robots on complex terrains unseen during the pre-training stage remains a challenge in robotics. Although general l…
- arXiv cs.AIresearchFlow Policy Gradients for Robot Control
arXiv:2602.02481v2 Announce Type: replace-cross Abstract: Likelihood-based policy gradient methods are the dominant approach for training robot control policies from rewards. These methods rely on differentiable action l…
- arXiv cs.AIresearchCoupled Local and Global World Models for Efficient First Order RL
arXiv:2602.06219v3 Announce Type: replace-cross Abstract: World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex sensory information,…
- arXiv cs.AIresearchOn the Dynamics of Delayed Generalization in Linear Models
arXiv:2602.08302v3 Announce Type: replace-cross Abstract: Delayed generalization, where training accuracy becomes nearly perfect substantially before test accuracy, has often been studied in the context of the depth and…
- arXiv cs.AIresearchCombining scEEG and PPG for reliable sleep staging
arXiv:2602.15042v2 Announce Type: replace-cross Abstract: Reliable sleep staging remains challenging for lightweight wearable devices such as single-channel electroencephalography (scEEG) or photoplethysmography (PPG). s…
- arXiv cs.AIresearchArticulated 3D Scene Graphs for Open-World Mobile Manipulation
arXiv:2602.16356v2 Announce Type: replace-cross Abstract: Semantic scene understanding has enabled robots to reason and perform affordance-driven object interaction. Despite this, real-world manipulation remains fundamen…
- arXiv cs.AIresearchPrompt Interference in LLM Post-Training: Why Pass@k Optimization Can Degrade Pass@1
arXiv:2602.21189v3 Announce Type: replace-cross Abstract: Pass@$k$ is a widely used performance metric for verifiable large language model tasks, including mathematical reasoning, code generation, and short-answer reason…
- arXiv cs.AIresearchAn Analysis of Role Semantics in Directed Dynamic Graph Modeling for Edge Classification
arXiv:2602.23135v3 Announce Type: replace-cross Abstract: Edge classification on directed dynamic graphs is critical for understanding evolving user-item interactions and behavioral patterns in recommender systems and so…
- arXiv cs.AIresearchToward Guarantees for Clinical Reasoning in Vision Language Models via Formal Verification
arXiv:2602.24111v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) show promise in drafting radiology reports, yet they frequently suffer from logical inconsistencies, generating diagnostic impressio…
- arXiv cs.AIresearchLearning Shortest Paths with Generative Flow Networks
arXiv:2603.01786v2 Announce Type: replace-cross Abstract: In this paper, we present a novel learning framework for finding shortest paths in graphs utilizing Generative Flow Networks (GFlowNets). First, we examine theore…
- arXiv cs.AIresearchCodecFlow: Efficient Bandwidth Extension via Conditional Flow Matching in Neural Codec Latent Space
arXiv:2603.02022v3 Announce Type: replace-cross Abstract: Speech Bandwidth Extension improves clarity and intelligibility by restoring/inferring appropriate high-frequency content for low-bandwidth speech. Existing metho…
- arXiv cs.AIresearchA Counterfactual Graph Approach to Oppositional Narrative Analysis
arXiv:2603.06135v3 Announce Type: replace-cross Abstract: Distinguishing legitimate critical speech from coordinated conspiracy narratives is a pressing challenge for the integrity of the online information ecosystem, ye…
- arXiv cs.AIresearchNeural-Surrogate Co-Design of Aerodynamic Shape and Control
arXiv:2603.06760v2 Announce Type: replace-cross Abstract: Control co-design jointly optimizes a robot's physical design and its controller. Existing techniques are limited in the number of model parameters and the comple…
- arXiv cs.AIresearchScheduling Parallel Optical Circuit Switches for AI Training
arXiv:2603.07373v2 Announce Type: replace-cross Abstract: The rapid growth of AI training has dramatically increased datacenter traffic demand and energy consumption, which has motivated renewed interest in optical circu…