AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAutoMind: Adaptive Knowledgeable Agent for Automated Data Science
arXiv:2506.10974v4 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents have shown great potential in addressing real-world data science problems. LLM-driven data science agents promise to automate th…
- arXiv cs.AIresearchChain of Retrieval: Multi-Aspect Iterative Search Expansion and Post-Order Search Aggregation for Full Paper Retrieval
arXiv:2507.10057v4 Announce Type: replace-cross Abstract: Scientific paper retrieval, particularly framed as document-to-document retrieval, aims to identify relevant papers in response to a long-form query paper, rather…
- arXiv cs.AIresearchNLP Meets the World: Toward Improving Conversations With News Media About Natural Language Processing Research
arXiv:2507.10559v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have rapidly increased the public's interest in natural language processing (NLP). This attention is reflected by…
- arXiv cs.AIresearchDynamic gain neuromodulation attenuates stability gaps during continual joint training
arXiv:2507.14056v4 Announce Type: replace-cross Abstract: Recent work in continual learning has highlighted the stability gap -- a temporary performance drop on previously learned tasks when new ones are introduced. This…
- arXiv cs.AIagentsThe Constitutional Controller: Doubt-Calibrated Steering of Compliant Agents
arXiv:2507.15478v2 Announce Type: replace-cross Abstract: Ensuring reliable and rule-compliant behavior of autonomous agents in uncertain environments remains a fundamental challenge in modern robotics. Our work shows ho…
- arXiv cs.AIresearchEquivariant Volumetric Grasping
arXiv:2507.18847v4 Announce Type: replace-cross Abstract: We propose a new volumetric grasp model that is equivariant to rotations around the vertical axis, leading to a significant improvement in sampling efficiency. Ou…
- arXiv cs.AIresearchSlotMatch: Distilling Object-Centric Representations for Unsupervised Video Segmentation
arXiv:2508.03411v4 Announce Type: replace-cross Abstract: Unsupervised video segmentation is a challenging computer vision task, especially due to the lack of supervisory signals coupled with the complexity of visual sce…
- arXiv cs.AIresearchOpen-sci-ref-0.02: open reference baselines for reproducible language model and dataset comparison
arXiv:2509.09009v4 Announce Type: replace-cross Abstract: Reliable progress in language modeling depends on knowing whether a new dataset, architecture, or training recipe is genuinely better than existing alternatives.…
- arXiv cs.AIresearchToward a Physics of Deep Learning and Brains
arXiv:2509.22649v2 Announce Type: replace-cross Abstract: Deep neural networks and brains both learn and share superficial similarities: processing nodes are likened to neurons and adjustable weights are likened to modif…
- arXiv cs.AIresearchVeriGRAG: Enhancing LLM-Based Verilog Code Generation with Structure-Aware Soft Prompts
arXiv:2510.15914v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in generating Verilog code from natural language descriptions. However, Verilog code inhere…
- arXiv cs.AIresearchThe Ends Justify the Thoughts: RL-Induced Motivated Reasoning Fools CoT Monitors
arXiv:2510.17057v3 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) monitoring has emerged as a compelling method for detecting harmful behaviors such as reward hacking in reasoning models, under the assumpt…
- arXiv cs.AIresearchManifold Approximation leads to Robust Kernel Alignment
arXiv:2510.22953v2 Announce Type: replace-cross Abstract: Centered kernel alignment (CKA) is a popular metric for comparing representations, determining equivalence of networks, and conducting neuroscience research. Howe…
- arXiv cs.AIresearchEngTrace: A Symbolic Benchmark for Verifiable Process Evaluation of Engineering Reasoning
arXiv:2511.01650v4 Announce Type: replace-cross Abstract: Most engineering problems involve complex multi-step derivations through checkable intermediate quantities. Grading only the final answer misjudges LLMs, creditin…
- arXiv cs.AIresearchA Privacy-Preserving Federated Learning Method for Heterogeneous Clients
arXiv:2511.06064v2 Announce Type: replace-cross Abstract: Federated Learning (FL) with Differential Privacy (DP) can ensure the protection of healthcare data privacy against malicious user attacks. However, FL with the D…
- arXiv cs.AIresearchContinually Evolving Skill Knowledge in Vision Language Action Model
arXiv:2511.18085v5 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models show promising knowledge accumulation ability through pretraining, yet continual learning remains challenging. Existing contin…
- arXiv cs.AIresearchCerium: A Multi-GPU Framework for Terabyte-Scale Encrypted Inference
arXiv:2512.11269v2 Announce Type: replace-cross Abstract: Encrypted AI using fully homomorphic encryption (FHE) enables inference directly over encrypted queries, providing strong privacy guarantees. However, its computa…
- arXiv cs.AIresearchIRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models
arXiv:2601.00677v3 Announce Type: replace-cross Abstract: Generative Reward Models (GRMs) have demonstrated strong performance in reward modeling, due to their interpretability and potential for refinement through reinfo…
- arXiv cs.AIresearchSteering Language Models Before They Speak: Logit-Level Interventions
arXiv:2601.10960v3 Announce Type: replace-cross Abstract: Controllable generation requires language models to realize output characteristics such as reading level, politeness, and toxicity. Existing steering methods are…
- arXiv cs.AIresearchPatch-Level Tokenization with CNN Encoders and Attention for Improved Transformer Time-Series Forecasting
arXiv:2601.12467v4 Announce Type: replace-cross Abstract: Transformer-based models have shown strong performance in time-series forecasting by leveraging self-attention to model long-range temporal dependencies. However,…
- arXiv cs.AIagentsAutomated structural testing of LLM-based agents: methods, framework, and case studies
arXiv:2601.18827v2 Announce Type: replace-cross Abstract: LLM-based agents are rapidly being adopted across diverse domains. Since they interact with users without supervision, they must be tested extensively. Current te…
- arXiv cs.AIresearchTest-Time Compute Games
arXiv:2601.21839v3 Announce Type: replace-cross Abstract: Test-time compute has emerged as a promising strategy to enhance the reasoning abilities of large language models (LLMs). However, this strategy has in turn incre…
- arXiv cs.AIresearchMachine Unlearning in Low-Dimensional Feature Subspace
arXiv:2601.22456v3 Announce Type: replace-cross Abstract: Machine Unlearning (MU) aims at removing the influence of specific data from a pretrained model while preserving performance on the remaining data. In this work,…
- arXiv cs.AIresearchTTCS: Test-Time Curriculum Synthesis for Self-Evolving
arXiv:2601.22628v3 Announce Type: replace-cross Abstract: Test-Time Training offers a promising way to improve the reasoning ability of large language models (LLMs) by adapting the model using only the test questions. Ho…
- arXiv cs.AIresearchMOSAIC: More LLMs, Less Cost through Collaborative Reasoning for Compiler Optimizations
arXiv:2602.01935v3 Announce Type: replace-cross Abstract: LLM-guided compiler optimization has recently shown promise. However, current LLM-guided optimizers query a single LLM at every search step, so their cost grows w…
- arXiv cs.AIresearchDo We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods
arXiv:2602.03802v2 Announce Type: replace-cross Abstract: Modern distributed optimization methods mostly rely on traditional synchronous approaches, despite substantial recent progress in asynchronous optimization. We re…
- arXiv cs.AIresearchSkin Tokens: A Learned Compact Representation for Unified Autoregressive Rigging
arXiv:2602.04805v2 Announce Type: replace-cross Abstract: The rapid proliferation of generative 3D models has created a critical bottleneck in animation pipelines: rigging. Existing automated methods are fundamentally li…
- arXiv cs.AIresearchSHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
arXiv:2602.06358v4 Announce Type: replace-cross Abstract: We propose SHINE (Scalable Hyper In-context NEtwork), a scalable hypernetwork that can map diverse meaningful contexts into high-quality LoRA adapters for large l…
- arXiv cs.AIresearchRAG Strategies for Natural Language-Based SQL Query and REST API Call Generation
arXiv:2602.07086v3 Announce Type: replace-cross Abstract: Enterprise software systems commonly expose functionality through relational databases and REST APIs, requiring users to understand schemas, endpoints, and parame…
- arXiv cs.AIresearchSLA2: Sparse-Linear Attention with Learnable Routing and Quantization-aware Training
arXiv:2602.12675v2 Announce Type: replace-cross Abstract: Sparse-Linear Attention (SLA) combines sparse and linear attention to accelerate diffusion models and has shown strong performance in video generation. However, (…
- arXiv cs.AIresearchPushing the Frontier of Black-Box LVLM Attacks via Fine-Grained Detail Targeting
arXiv:2602.17645v2 Announce Type: replace-cross Abstract: Black-box adversarial attacks on Large Vision-Language Models (LVLMs) are challenging due to missing gradients and complex multimodal boundaries. Prior state-of-t…
- arXiv cs.AIresearchWhat Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI
arXiv:2602.20547v2 Announce Type: replace-cross Abstract: Conversational AI tools have been rapidly adopted by students and are becoming part of their learning routines. This widespread use comes amid ongoing concerns ab…
- arXiv cs.AIresearchGRAU: A Generic Runtime-Reconfigurable Activation-Requantization Unit for Quantized Neural Network Accelerators
arXiv:2602.22352v3 Announce Type: replace-cross Abstract: As neural networks continue to scale, low-precision quantization is widely adopted in edge accelerators, but conventional multi-threshold activation hardware requ…
- arXiv cs.AIresearchBrain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG
arXiv:2602.23410v4 Announce Type: replace-cross Abstract: Brain foundation models have achieved remarkable advances across a wide range of neuroscience tasks. However, most existing models are limited to a single functio…
- arXiv cs.AIresearchDifferential privacy representation geometry for medical image analysis
arXiv:2603.01098v4 Announce Type: replace-cross Abstract: Differential privacy (DP)'s effect in medical imaging is typically evaluated only through end-to-end performance, leaving the mechanism of privacy-induced utility…
- arXiv cs.AIresearchRigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles
arXiv:2603.02406v3 Announce Type: replace-cross Abstract: Generative models have recently advanced $\textit{de novo}$ protein design by learning the statistical regularities of natural structures. However, current approa…
- arXiv cs.AIresearchRoboPocket: Improve Robot Policies Instantly with Your Phone
arXiv:2603.05504v3 Announce Type: replace-cross Abstract: Scaling robot learning is bottlenecked not only by data volume, but also by whether the data targets the policy's failures. Existing robot-free handheld interface…
- arXiv cs.AIagentsAgentic AI -- Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data
arXiv:2603.05735v3 Announce Type: replace-cross Abstract: We present an agentic measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s}=91.2$ GeV using ALEPH archived data. This work was carried ou…
- arXiv cs.AIagentsKernelClaw: A Multi-Agent Framework for GPU Kernel Optimization with Dual-Memory Mechanisms
arXiv:2603.10085v2 Announce Type: replace-cross Abstract: Improving GPU kernel efficiency is crucial for efficient AI systems. Recent work has explored leveraging large language models (LLMs) for GPU kernel generation an…
- arXiv cs.AIresearchBrittlebench: Quantifying LLM robustness via prompt sensitivity
arXiv:2603.13285v4 Announce Type: replace-cross Abstract: Existing evaluation methods largely rely on clean, static benchmarks, which can overestimate true model performance by failing to capture the noise and variabilit…
- arXiv cs.AIresearchBridging the Gap in the Responsible AI Divides
arXiv:2603.14495v2 Announce Type: replace-cross Abstract: Tensions between AI Safety (AIS) and AI Ethics (AIE) have created what we term a "responsible AI divide." This divide has been persistent, and has dominated the p…
- arXiv cs.AIresearchSF-Mamba: Rethinking State Space Model for Vision
arXiv:2603.16423v2 Announce Type: replace-cross Abstract: Visual Mamba models have recently emerged as alternatives to Vision Transformers (ViTs), which suffer from quadratic complexity. While the recurrent scanning mech…
- arXiv cs.AIresearchAttention Sinks Induce Gradient Sinks: Massive Activations as Gradient Regulators in Transformers
arXiv:2603.17771v3 Announce Type: replace-cross Abstract: Attention sinks and massive activations are recurring and closely related phenomena in Transformer models. Existing explanations have largely focused on the forwa…
- arXiv cs.AIresearchEVA: Aligning Video World Models with Executable Robot Actions via Inverse Dynamics Rewards
arXiv:2603.17808v3 Announce Type: replace-cross Abstract: Video generative models offer a promising basis for robotic planning by predicting future visual rollouts from observations and task instructions. However, their…
- arXiv cs.AIresearchSpan-Level Machine Translation Meta-Evaluation
arXiv:2603.19921v2 Announce Type: replace-cross Abstract: Machine Translation (MT) and automatic MT evaluation have improved dramatically in recent years, enabling numerous novel applications. Automatic evaluation techni…
- arXiv cs.AIresearchCTFS : Collaborative Teacher Framework for Forward-Looking Sonar Image Semantic Segmentation with Extremely Limited Labels
arXiv:2603.21071v3 Announce Type: replace-cross Abstract: As one of the most important underwater sensing technologies, forward-looking sonar exhibits unique imaging characteristics. Sonar images are often affected by se…
- arXiv cs.AIresearchEstimating Individual Tree Height and Species from UAV Imagery
arXiv:2603.23669v3 Announce Type: replace-cross Abstract: Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial Vehicles (UAVs) capt…
- arXiv cs.AIagentsOccSim: Multi-kilometer Simulation with Long-horizon Occupancy World Models
arXiv:2603.28887v2 Announce Type: replace-cross Abstract: Data-driven autonomous driving simulation has long been constrained by its heavy reliance on pre-recorded driving logs or spatial priors, such as HD maps. This fu…
- arXiv cs.AIresearchDerived Fields Increase the Recoverable Information in Budgeted Neural PDE Surrogate
arXiv:2603.29224v2 Announce Type: replace-cross Abstract: For neural surrogates of time-dependent partial differential equations (PDEs), storage and memory budgets require training data to be obtained by coarsening and q…
- arXiv cs.AIresearchBringing Up a Bilingual BabyLM: Investigating Multilingual Language Acquisition Using Small-Scale Models
arXiv:2603.29552v3 Announce Type: replace-cross Abstract: Multilingualism is incredibly common around the world, leading to many important theoretical and practical questions, including whether multilingual acquisition l…
- arXiv cs.AIagentsCausal Scene Narration: Inference-Time Text Restructuring for Vision-Language-Action Driving
arXiv:2604.01723v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models for autonomous driving receive navigation commands and hazard notices as disconnected text fragments, forcing the model to dis…