AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchTeaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization
arXiv:2606.07000v2 Announce Type: replace Abstract: Recent post-training methods, particularly Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced the reasoning ability of Large Vision-Lang…
- arXiv cs.AIagentsAgentic vs. Parametric World Models: Hybrid Planning for Reliable Language Agents
arXiv:2606.27806v4 Announce Type: replace Abstract: Language agents, such as ReAct, Reflexion, and RAP, implicitly predict how the world will change as they plan and act, using imagined state transitions to guide their d…
- arXiv cs.AIagentsAsk the World Before Acting: Environment Probing for Calibrating Agent World Models
arXiv:2606.31422v3 Announce Type: replace Abstract: Long-horizon language agents enable autonomous decision-making in complex environments by planning and executing sequences of interdependent actions. To act reliably, t…
- arXiv cs.AIagentsRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents
arXiv:2607.01767v3 Announce Type: replace Abstract: Long-horizon language agents make interdependent decisions across multiple rounds, forming growing planning graphs in which later decisions depend on earlier states, ob…
- arXiv cs.AIresearchAIMO Interpretability Challenge
arXiv:2607.13899v2 Announce Type: replace Abstract: We propose the AIMO Interpretability Challenge, a competition on distinguishing robust from spurious reasoning in frontier mathematical language models based on the mod…
- arXiv cs.AIagentsIDEAgent: Agentic Quality-Diversity Search for Research Idea Generation
arXiv:2607.22375v2 Announce Type: replace Abstract: Large Language Models (LLMs) have significantly advanced the automation of scientific discovery. However, existing systems share a core limitation: they optimize ideas…
- arXiv cs.AIagentsCoordinated Networking for On-Device Agent-Augmented Real-Time Communication
arXiv:2607.22854v2 Announce Type: replace Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents autonomously retrie…
- arXiv cs.AIresearchIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD
arXiv:2607.28050v2 Announce Type: replace Abstract: Automating industrial CAD design and manufacturing places distinctive demands on multimodal foundation models: the model must see engineering drawings and 3D geometry s…
- arXiv cs.AIagentsECHO: An Auditable Dual-Path Memory System for Long-Horizon Agents
arXiv:2608.21755v2 Announce Type: replace Abstract: Long-horizon agents require more than retrieval over stored conversations: they must preserve source evidence, revise outdated knowledge, and distinguish relevant memor…
- arXiv cs.AIresearchEthical LLM-Assisted Research: A Framework for Responsible Delegation, Verification, and Epistemic Value
arXiv:2608.23644v2 Announce Type: replace Abstract: Large language models (LLMs) are becoming routine instruments of scientific research, assisting with literature synthesis, hypothesis development, coding, and formal re…
- arXiv cs.AIagentsUnified Agentic Video Editing Across Levels of Complexity and Creativity
arXiv:2609.12769v3 Announce Type: replace Abstract: Editing is a core component of video production, requiring creative planning and decisions under multiple constraints. Here, we report methods for agentic tooling for a…
- arXiv cs.AIresearchER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models
arXiv:2609.15089v2 Announce Type: replace Abstract: In human conversation, empathy involves not only recognizing a partner's emotion but also regulating it, listeners identify the emotional state, select a suitable regul…
- arXiv cs.AIresearchTaskonomy: Disentangling Task Transfer Learning
arXiv:1804.08328v2 Announce Type: replace-cross Abstract: Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answer…
- arXiv cs.AIresearchTyphoon: Gradient-Based Task-Specific Masking for Masked Language Models
arXiv:2303.15619v3 Announce Type: replace-cross Abstract: The choice of which tokens to mask is an under-examined design decision in masked language modeling (MLM). Standard pretraining masks tokens uniformly at random,…
- arXiv cs.AIresearchEntropic perspective on AI resilience, data-minimal learning and optimal control
arXiv:2310.14421v5 Announce Type: replace-cross Abstract: Behind the general terms like adversarial attacks and generative adversarial networks (GANs), such criteria as AI resilience and AI robustness gained a crucial im…
- arXiv cs.AIresearchJacobian Descent for Multi-Objective Optimization
arXiv:2406.16232v4 Announce Type: replace-cross Abstract: Many optimization problems require balancing multiple conflicting objectives. To generalize gradient descent, which is limited to single-objective optimization, w…
- arXiv cs.AIresearchDeep learning-based multi-level airway collapse site localization on obstructive sleep apnea patients based on snoring sounds
arXiv:2408.16030v3 Announce Type: replace-cross Abstract: Objective This study evaluated deep learning models, specifically ResNet-50 and Audio Spectrogram Transformer (AST), to identify multi-level upper airway collapse…
- arXiv cs.AIresearchSynergistic Action and Style Priors for Learning Legged Locomotion
arXiv:2410.03246v3 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) enables robots to learn complex behaviors through interaction with the environment. However, due to the unrestricted nature of t…
- arXiv cs.AIresearchPALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models
arXiv:2503.18462v2 Announce Type: replace-cross Abstract: Deep generative models (DGMs) have caused a paradigm shift in the field of machine learning, yielding noteworthy advancements in domains such as image synthesis,…
- arXiv cs.AIresearchA Survey of Generative Categories and Techniques in Multimodal Generative Models
arXiv:2506.10016v4 Announce Type: replace-cross Abstract: Multimodal generative models (MGMs) have rapidly expanded beyond text generation to encompass images, music, video, human motion, and 3D objects. This survey cate…
- arXiv cs.AIresearchWoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations
arXiv:2508.20976v2 Announce Type: replace-cross Abstract: Large audio-language models (LALMs) extend language understanding into the auditory domain, yet their ability to perform low-level listening, such as pitch and du…
- arXiv cs.AIresearchAttention-Aligned Reasoning for Large Language Models
arXiv:2510.03223v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) tend to generate a long reasoning chain when solving complex tasks. However, as the reasoning chain extends, critical intermediate st…
- arXiv cs.AIresearchBayesian Nonparametric Dynamical Clustering of Time Series
arXiv:2510.06919v2 Announce Type: replace-cross Abstract: We present a method that models the evolution of an unbounded number of time series clusters by switching among an unknown number of regimes with linear dynamics.…
- arXiv cs.AIresearchOnline Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network
arXiv:2511.01553v3 Announce Type: replace-cross Abstract: Edge AI must adapt to new classes and shifting data within a tight power budget, but online continual learning (learning from each sample before the next arrives)…
- arXiv cs.AIresearchSpectralTrain: A Universal Framework for Hyperspectral Image Classification
arXiv:2511.16084v4 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification typically involves large-scale data and computationally intensive training, which limits the practical deployment of deep…
- arXiv cs.AIagentsFrom Crawled to Published: A Publisher-Controlled Web Architecture for an AI-Native Internet
arXiv:2511.18354v2 Announce Type: replace-cross Abstract: AI agents, not humans, are becoming the web's primary consumers, yet the web still ships content structured for human browsing, with no native way for publishers…
- arXiv cs.AIresearchWhen does Subgroup Balance Matter? Predicting Performance Sensitivity from Latent Separability
arXiv:2512.09496v2 Announce Type: replace-cross Abstract: Unequal representation of demographic groups in training data poses challenges to model generalisation across populations. Standard practice assumes that balancin…
- arXiv cs.AIresearchOPTIMA: Optimal One-shot Pruning for LLMs via Quadratic Programming Reconstruction
arXiv:2512.13886v3 Announce Type: replace-cross Abstract: Post-training pruning cuts the inference cost of large language models, yet it faces a trade-off: simple heuristics that zero weights are fast but degrade accurac…
- arXiv cs.AIresearchReinforced Linear Genetic Programming
arXiv:2601.09736v2 Announce Type: replace-cross Abstract: Linear Genetic Programming (LGP) is a powerful technique that allows for a variety of problems to be solved using a linear representation of programs. However, th…
- arXiv cs.AIresearchActivation Sensitivity as a Unifying Principle for Post-Training Quantization
arXiv:2601.11663v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) methods for large language models compress pretrained weights to low bit-widths without retraining by optimizing layer-local prox…
- arXiv cs.AIresearchExpected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
arXiv:2601.21669v2 Announce Type: replace-cross Abstract: Many reinforcement learning (RL) problems admit multiple terminal solutions of comparable quality, where the goal is not to identify a single optimum but to repre…
- arXiv cs.AIresearchGraph-Theoretic Formulation of Hamiltonian and Ground-State Sign Structures in Heisenberg Antiferromagnets
arXiv:2602.04943v5 Announce Type: replace-cross Abstract: We study Heisenberg antiferromagnets through a graph-theoretic representation of their Hamiltonians. In the computational basis of a fixed-magnetization sector, t…
- arXiv cs.AIresearchCHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning
arXiv:2603.00889v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have exhibited remarkable reasoning capabilities, largely enabled by supervised fine-tuning (SFT)- and reinforcement learning (RL)-ba…
- arXiv cs.AIresearchAnchoring and Rescaling Attention for Semantically Coherent Inbetweening
arXiv:2603.17651v2 Announce Type: replace-cross Abstract: Generative inbetweening (GI) seeks to synthesize realistic intermediate frames between the first and last keyframes beyond mere interpolation. As sequences become…
- arXiv cs.AIresearchDetection Is Cheap, Routing Is Learned: Why Refusal-Based Alignment Evaluation Fails
arXiv:2603.18280v4 Announce Type: replace-cross Abstract: Current alignment evaluation mostly measures whether models encode dangerous concepts and whether they refuse harmful requests. Both miss the layer where alignmen…
- arXiv cs.AIresearchInterpretable PM2.5 Forecasting for Urban Air Quality: A Comparative Study of Adaptive Time-Series Models
arXiv:2603.25495v2 Announce Type: replace-cross Abstract: Accurate short-term air-quality forecasting is essential for public health protection and urban management, yet many recent forecasting frameworks rely on complex…
- arXiv cs.AIresearchAbstract Compression of Conversational Audio Context for LLM-based ASR
arXiv:2603.26246v2 Announce Type: replace-cross Abstract: Standard LLM-based speech recognition systems process utterances in isolation, limiting their ability to leverage conversational context. Here we study whether mu…
- arXiv cs.AIresearchLLaVA-CKD: Bottom-Up Cascaded Knowledge Distillation for Vision-Language Models
arXiv:2605.10641v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (VLMs) are successful in addressing a multitude of vision-language understanding tasks, such as Visual Question Answering (VQA), but…
- arXiv cs.AIresearchDynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning
arXiv:2605.10765v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, yet real-world deployment often requires continual capability expa…
- arXiv cs.AIresearchCounterCount: Diagnosing Knowledge Bias in How Vision-Language Models Count Attributes
arXiv:2605.17826v2 Announce Type: replace-cross Abstract: Do Vision-Language Models (VLMs) count what they see, or what they know about the world? We introduce CounterCount, a diagnostic dataset of paired factual and cou…
- arXiv cs.AIresearchDynamic Model Merging Made Slim
arXiv:2605.18904v2 Announce Type: replace-cross Abstract: Model merging consolidates independently fine-tuned checkpoints without joint training or access to task data. Dynamic methods retain task-specific capacity, but…
- arXiv cs.AIresearchDEFLECT: Temporal Counterfactual Preference Learning for Delay-Robust Asynchronous VLAs
arXiv:2605.19294v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) policies increasingly rely on asynchronous inference to hide model latency behind ongoing robot motion. During inference, the robot c…
- arXiv cs.AIresearchNVIDIA Spectrum-X: Hardware-Accelerated Multiplane Networking for Large-Scale AI Training
arXiv:2605.21187v2 Announce Type: replace-cross Abstract: As distributed model training scales to span hundreds of thousands of GPUs, scale-out networks face unprecedented performance and efficiency demands. NVIDIA Spect…
- arXiv cs.AIresearchWhat a One-Hour Interview Does Not Tell an LLM About You: Interviews Elicit Traits, Not Decision Policies
arXiv:2605.29458v2 Announce Type: replace-cross Abstract: Large language models are increasingly asked to stand in for particular people, and interviewing the person is the natural way to tell a model who they are. We te…
- arXiv cs.AIresearchSame Evidence, Different Answers: Canonical-Context On-Policy Distillation for Multi-Turn Language Models
arXiv:2605.30251v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often solve a task when all instructions are given in a single prompt, but fail when the same information is revealed gradually acros…
- arXiv cs.AIresearchFlow Control: Steering Vision-Language-Action Models with Simple Real-Time Inputs
arXiv:2606.10180v2 Announce Type: replace-cross Abstract: We introduce flow control of vision-language-action (VLA) models, a simple and effective way to steer VLA actions in real time through generic inputs, such as a k…
- arXiv cs.AIresearchKITE: Decoupling Kinematics and Interaction for Zero-Shot Cross-Embodiment Manipulation
arXiv:2606.22113v2 Announce Type: replace-cross Abstract: Generalizing manipulation policies across robot embodiments remains difficult because standard policies tie the interactions needed for a task to the actions of a…
- arXiv cs.AIresearchYuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety
arXiv:2606.25034v3 Announce Type: replace-cross Abstract: General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature o…
- arXiv cs.AIagentsFor Coding Agents, the Repository Matters
arXiv:2606.28235v2 Announce Type: replace-cross Abstract: In July 2026, about 1,200 AI agents in an internal OpenAI evaluation, meant to run in isolation, used a shared package server as a message board, and about 700 of…
- arXiv cs.AIresearchProbe, Don't Prompt: A Hidden-State Probe for Metadata Filtering in Multi-Meta-RAG
arXiv:2607.03929v2 Announce Type: replace-cross Abstract: Multi-Meta-RAG improves retrieval for multi-hop question answering by filtering a vector store on metadata, specifically the news source and the publication date,…