AI news archive.
10,660 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchRethinking Patch Based Multivariate Time Series Forecasting with Semantic Structured Partitioning
arXiv:2608.19966v2 Announce Type: replace Abstract: Multivariate time series forecasting (MTSF) is a fundamental task in many real world applications. Existing patch based forecasting methods generally fall into three ca…
- arXiv cs.AIresearchSolving Robust POMDPs with Omega-regular Objectives via Partially Observable Stochastic Games
arXiv:2608.24986v2 Announce Type: replace Abstract: Robust POMDPs (RPOMDPs) generalize classical POMDPs to the setting where exact transition probabilities are not known -- rather, they are only known to belong to some u…
- arXiv cs.AIresearchVision Is Not Overhead: One-Pass Block Drafting for Lossless Speculative Decoding in Vision-Language Models
arXiv:2609.00355v3 Announce Type: replace Abstract: Speculative decoding accelerates generation without changing its output, but on vision-language models (VLMs) a self-reinforcing cycle holds it back. Because an autoreg…
- arXiv cs.AIresearchHow Should Reasoning Be Organized in a Transformer's Latent Space?
arXiv:2609.13747v2 Announce Type: replace Abstract: Continuous reasoning has emerged as a promising way to improve reasoning in large language models (LLMs). Yet we still lack a clear principle for deciding what a latent…
- arXiv cs.AIresearchOn the Approximation and Convergence of Distributional Policy Gradient Algorithms for Risk-Sensitive Reinforcement Learning
arXiv:2405.14749v3 Announce Type: replace-cross Abstract: Risk-sensitive reinforcement learning (RL) is crucial for maintaining reliable performance in high-stakes applications. While traditional RL methods aim to learn…
- arXiv cs.AIresearchBadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models
arXiv:2406.00083v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge bases to provide more accura…
- arXiv cs.AIresearchRecKG: Knowledge Graph for Recommender Systems
arXiv:2501.03598v2 Announce Type: replace-cross Abstract: Knowledge graphs have proven successful in integrating heterogeneous data across various domains. However, there remains a noticeable dearth of research on their…
- arXiv cs.AIresearchCausal pieces: analysing and improving spiking neural networks piece by piece
arXiv:2504.14015v2 Announce Type: replace-cross Abstract: We introduce "causal pieces", a novel concept for analysing spiking neural networks (SNNs), inspired by "linear pieces" used to study expressivity and trainabilit…
- arXiv cs.AIresearchMoCA-Video: Motion-Aware Concept Alignment for Consistent Video Editing
arXiv:2506.01004v3 Announce Type: replace-cross Abstract: Unlike traditional video editing or inpainting, video semantic mixing fuses a reference concept with a moving target entity to produce a hybrid while preserving t…
- arXiv cs.AIresearchGondola: Grounded Vision Language Planning for Robotic Manipulation
arXiv:2506.11261v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have shown promising progress in robotic manipulation. However, directly mapping visual observations and language instructions…
- arXiv cs.AIresearchLearning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning
arXiv:2507.12612v5 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set of tasks. In practi…
- arXiv cs.AIresearchLLM Serving Optimization with Variable Prefill and Decode Lengths
arXiv:2508.06133v5 Announce Type: replace-cross Abstract: We study offline scheduling for large language model (LLM) serving under a fixed KV-cache memory budget, where requests have heterogeneous prompt (prefill) and re…
- arXiv cs.AIresearchMitigating Cross-Image Information Leakage in Multi-Image Understanding with Large Vision-Language Models
arXiv:2508.13744v3 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) exhibit strong performance on single-image tasks. However, their performance degrades significantly when handling multi-image…
- arXiv cs.AIresearchGeometrically Constrained and Token-Based Probabilistic Spatial Transformers
arXiv:2509.11218v3 Announce Type: replace-cross Abstract: Spatial transformations such as rotation and scale obscure the morphological cues needed for accurate image classification. Careful consideration is required for…
- arXiv cs.AIresearchAdversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation
arXiv:2509.20411v3 Announce Type: replace-cross Abstract: Machine learning-based cybersecurity systems are highly vulnerable to adversarial attacks, while Generative Adversarial Networks (GANs) act as both powerful attac…
- arXiv cs.AIresearchHybrid Approach for Enhancing Lesion Segmentation in Fundus Images
arXiv:2509.25549v3 Announce Type: replace-cross Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to improving survival…
- arXiv cs.AIresearchCPATTA: Conformal Supervision Allocation For Active Test-Time Adaptation
arXiv:2509.25692v2 Announce Type: replace-cross Abstract: Active Test-Time Adaptation (ATTA) improves model robustness under domain shift by selectively querying human annotations at deployment, but existing methods use…
- arXiv cs.AIresearchBeyond Semantics: How Temporal Biases Shape Retrieval in Transformer and State-Space Models
arXiv:2510.22752v2 Announce Type: replace-cross Abstract: In-context learning is governed by both temporal and semantic relationships, shaping how Large Language Models (LLMs) retrieve contextual information. Analogous t…
- arXiv cs.AIresearchEvidence-Guided Schema Normalization for Temporal Tabular Reasoning
arXiv:2512.00329v2 Announce Type: replace-cross Abstract: Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose an approach that recasts the task as automated knowled…
- arXiv cs.AIresearchTraining-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation
arXiv:2512.18991v3 Announce Type: replace-cross Abstract: Dominant paradigms for 4D LiDAR panoptic segmentation are usually required to train deep neural networks with large superimposed point clouds or design dedicated…
- arXiv cs.AIresearchData-Free Pruning of Self-Attention Layers in LLMs
arXiv:2512.20636v2 Announce Type: replace-cross Abstract: Many self-attention sublayers in large language models (LLMs) can be removed with little to no loss. We attribute this to the Attention Suppression Hypothesis: du…
- arXiv cs.AIresearchAsymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling
arXiv:2601.08777v2 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for personalized and trustw…
- arXiv cs.AIresearchUncertainty-aware Causal Decision Making via Effect Bound Decomposition
arXiv:2601.22736v3 Announce Type: replace-cross Abstract: Causal inference from observational data can provide strong evidence for finding the best action in a decision-making scenario without having to perform expensive…
- arXiv cs.AIresearchPhaedra: Learning High-Fidelity Discrete Tokenization for the Physical Science
arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be efficiently learned,…
- arXiv cs.AIresearchFrom Concept Erasure to Style Purification: Contrastive Eigenbases for Artist Style Protection
arXiv:2602.08059v2 Announce Type: replace-cross Abstract: Text-to-image diffusion models can reproduce specific artists visual styles at extremely low cost, raising copyright and deployment safety concerns about unauthor…
- arXiv cs.AIresearchOn Calibration of Large Language Models: From Response To Capability
arXiv:2602.13540v2 Announce Type: replace-cross Abstract: Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on response-level confi…
- arXiv cs.AIresearchRobo-Saber: Generating and Simulating Virtual Reality Players
arXiv:2602.18319v2 Announce Type: replace-cross Abstract: We present the first motion generation system for playtesting virtual reality (VR) games. Our player model generates VR headset and handheld controller movements…
- arXiv cs.AIresearchCOMiT: Learning Structured Visual Tokens through Sequential Communication
arXiv:2602.20731v2 Announce Type: replace-cross Abstract: Discrete image tokenizers provide a sequential interface for vision and multimodal models, but are typically optimized for reconstruction or compression and there…
- arXiv cs.AIresearchContactExplorer: Contact Coverage-Guided Exploration for General-Purpose Dexterous Manipulation
arXiv:2603.10971v4 Announce Type: replace-cross Abstract: Reinforcement learning explores effectively in domains such as Atari games, navigation, and locomotion, where novelty over states or dynamics is a sufficient sign…
- arXiv cs.AIresearchAltered Thoughts, Altered Actions: Reasoning Chain as Control Surface for a Vision-Language-Action Policy
arXiv:2603.12717v3 Announce Type: replace-cross Abstract: Vision-language-action policies map camera images and natural-language instructions to a robot's motor actions. Some of these policies are designed to reason in t…
- arXiv cs.AIresearchTabKD: Tabular Knowledge Distillation through Interaction Diversity of Learned Feature Bins
arXiv:2603.15481v3 Announce Type: replace-cross Abstract: Data-free knowledge distillation enables model compression without original training data, critical for privacy-sensitive tabular domains. However, existing metho…
- arXiv cs.AIresearchPure and physics-guided deep learning approaches for spatio-temporal groundwater level prediction
arXiv:2603.25779v2 Announce Type: replace-cross Abstract: Groundwater represents a key element of the water cycle, yet it exhibits complex and context-dependent relationships that make its modeling challenging. Theory-ba…
- arXiv cs.AIresearchScreening Is Enough
arXiv:2604.01178v4 Announce Type: replace-cross Abstract: We call query--key relevance absolute when its values lie on a fixed bounded scale, depend on neither competing keys nor sequence length, require no sequence-leng…
- arXiv cs.AIresearchSuppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs
arXiv:2604.03114v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) may need to forget visual concepts after deployment because of privacy, copyright, licensing, safety, or policy changes. Conventiona…
- arXiv cs.AIresearchRevisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective
arXiv:2604.08880v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) distillation transfers reasoning behaviors from a strong teacher to a smaller student, but prior work reports a capacity gap: distillation…
- arXiv cs.AIresearchQuery Lower Bounds for Diffusion Sampling
arXiv:2604.10857v2 Announce Type: replace-cross Abstract: Diffusion models generate samples by iteratively querying learned score estimates. A rapidly growing literature focuses on accelerating sampling by minimizing the…
- arXiv cs.AIresearchPAC-CF: Calibrating Irreversible Frontier Pruning in LLM-Guided Search
arXiv:2604.14345v5 Announce Type: replace-cross Abstract: LLM-guided search explores multiple candidate trajectories, but at substantial test-time cost. Pruning low-scoring frontier candidates can control this cost, yet…
- arXiv cs.AIresearchAmortized Optimal Transport from Sliced Potentials
arXiv:2604.15114v2 Announce Type: replace-cross Abstract: We propose a novel amortized optimization method for predicting optimal transport (OT) plans across multiple pairs of measures by leveraging Kantorovich potential…
- arXiv cs.AIresearchReplay-buffer engineering for noise-aware quantum circuit optimization
arXiv:2604.21863v2 Announce Type: replace-cross Abstract: Deep reinforcement learning for quantum circuit optimization faces three bottlenecks: replay buffers that overlook temporal difference (TD) target reliability, cu…
- arXiv cs.AIresearchUtility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs
arXiv:2604.22893v2 Announce Type: replace-cross Abstract: Traditional ``row-count $\times$ quality coefficient'' approaches fail to capture the nonlinear utility of data for Large Language Model (LLM) capabilities. We pr…
- arXiv cs.AIresearchUnderstanding Scattered Forest Search: A Version-Space Perspective on Multi-Turn Program Correction
arXiv:2604.23989v3 Announce Type: replace-cross Abstract: In multi-turn program correction, the state-of-the-art method Scattered Forest Search (SFS) has been proposed, employing Monte Carlo Tree Search (MCTS) with caref…
- arXiv cs.AIresearchSingle-turn emergency psychiatric triage across 15 frontier AI chatbots
arXiv:2604.25415v3 Announce Type: replace-cross Abstract: People increasingly turn to general-purpose AI chatbots for advice about emotional and mental health problems, but the ability of these systems to recognize and a…
- arXiv cs.AIresearchGRAVITY: Architecture-Agnostic Structured Anchoring for Long-Horizon Conversational Memory
arXiv:2605.01688v2 Announce Type: replace-cross Abstract: Long-horizon memory systems increasingly improve how evidence is stored and retrieved, yet the generator must still reason over fragments whose cross-session rela…
- arXiv cs.AIresearchCumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant
arXiv:2605.06240v2 Announce Type: replace-cross Abstract: Forward-Forward (FF) training lets each layer learn from a local goodness criterion. In cumulative-goodness variants, later layers can inherit a task that earlier…
- arXiv cs.AIresearchNoiseRater: Meta-Learned Noise Valuation for Diffusion Model Training
arXiv:2605.08144v2 Announce Type: replace-cross Abstract: Training a diffusion model involves two sources of randomness for each data sample: the timestep and the Gaussian noise realization. The timestep has been studied…
- arXiv cs.AIresearchPowerStep: Memory-Efficient Adaptive Optimization via $\ell_p$-Norm Steepest Descent
arXiv:2605.10335v2 Announce Type: replace-cross Abstract: Adaptive optimizers such as Adam are standard for training Transformers, but storing gradient first and second moments incurs substantial memory overhead. We intr…
- arXiv cs.AIresearchPRISM: A Geometric Risk Bound for Decomposing Drift into Scale, Shape, and Head
arXiv:2605.11608v2 Announce Type: replace-cross Abstract: A single base LLM now comes with dozens of post-training variants, quantized, LoRA-adapted, or distilled, and each has to be checked before release. Existing eval…
- arXiv cs.AIresearchGenerative Support Realignment for Cross-Domain Offline Reinforcement Learning
arXiv:2605.13054v2 Announce Type: replace-cross Abstract: Cross-domain offline reinforcement learning learns a target policy from pre-collected source and target datasets with different dynamics. When target data are sca…
- arXiv cs.AIresearchFactorizedHMR: A Hybrid Framework for Video Human Mesh Recovery
arXiv:2605.14854v4 Announce Type: replace-cross Abstract: Human Mesh Recovery (HMR) is fundamentally ambiguous: under occlusion or weak depth cues, multiple 3D bodies can explain the same image evidence. This ambiguity i…
- arXiv cs.AIresearchEdge-AI-Driven Learning-to-Rank for Decentralized Task Allocation in Circular Smart Manufacturing
arXiv:2605.16433v4 Announce Type: replace-cross Abstract: Task allocation in smart manufacturing systems must operate under decentralized decision-making, dynamic workloads, and shared-resource constraints. In circular m…