AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchBenchmarking the Personalization Capabilities of Large Language Models
arXiv:2607.20471v2 Announce Type: replace Abstract: Personalization is classically a two-party problem: a sender chooses what to say, and a receiver with independent objectives decides whether to act. A salesperson pitch…
- arXiv cs.AIresearchRefusal-Gated Decoding: Preserving Refusal Behavior Under High-Temperature Sampling
arXiv:2607.20791v2 Announce Type: replace Abstract: Recent advances in truncation-based sampling have helped mitigate drawbacks of high-temperature sampling such as neural text degeneration, thereby enabling greater dive…
- arXiv cs.AIresearchRethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations
arXiv:2608.03611v3 Announce Type: replace Abstract: Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplete. Existing meth…
- arXiv cs.AIresearchWebRider: Persona-Conditioned Intent Controllers for Live-Web Assistance
arXiv:2608.06704v2 Announce Type: replace Abstract: Delegating a web task involves more than asking a question; it requires transferring a policy: what to verify, how to handle uncertainty, which preferences matter, and…
- arXiv cs.AIresearchPost-Grokking Collapse at the Representation-Readout Interface in Muon-Trained Transformers
arXiv:2608.07436v2 Announce Type: replace Abstract: Muon-trained modular-arithmetic transformers can lose accuracy while retaining linearly decodable task information. Adjacent swaps localize five captured unnormalized f…
- arXiv cs.AIagentsUnitBoost: Managing Compound LLM Systems with a Merge Operator, Not a Model
arXiv:2609.09815v2 Announce Type: replace Abstract: Compound LLM systems often solve a coordination problem by adding a higher-level LLM. The resulting meta-agent reads workers' outputs, writes the final answer, allocate…
- arXiv cs.AIresearchFast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields
arXiv:2311.18029v2 Announce Type: replace-cross Abstract: The current trend in the literature on Time Series Classification is to develop increasingly accurate algorithms by combining multiple models in ensemble hybrids,…
- arXiv cs.AIresearchHypergraph-Enhanced Dual Convolutional Network for Bundle Recommendation
arXiv:2312.11018v4 Announce Type: replace-cross Abstract: Bundle recommendation ranks sets of related items rather than isolated items. Its central challenge is to connect user preferences, item interactions, and bundle…
- arXiv cs.AIresearchFreDF: Learning to Forecast in the Frequency Domain
arXiv:2402.02399v3 Announce Type: replace-cross Abstract: Time series modeling presents unique challenges due to autocorrelation in both historical data and future sequences. While current research predominantly addresse…
- arXiv cs.AIresearchDiffusion Model-Based Video Editing: A Survey
arXiv:2407.07111v2 Announce Type: replace-cross Abstract: The rapid development of diffusion models (DMs) has significantly advanced image and video applications, making "what you want is what you see" a reality. Among t…
- arXiv cs.AIresearchModeling Time-Dependent Responses of Optical Compressors with Selective State Space Models
arXiv:2408.12549v4 Announce Type: replace-cross Abstract: This paper presents a method for modeling optical dynamic range compressors using deep neural networks with Selective State Space models. The proposed approach su…
- arXiv cs.AIresearchLarge Pretraining Datasets Don't Guarantee Robustness after Fine-Tuning in Image Classification
arXiv:2410.21582v4 Announce Type: replace-cross Abstract: Large-scale pretrained models are widely leveraged as foundations for learning new specialized tasks via fine-tuning, with the goal of maintaining the general per…
- arXiv cs.AIresearchBoosting Large Language Models with Mask Fine-Tuning
arXiv:2503.22764v3 Announce Type: replace-cross Abstract: The large language model (LLM) is typically integrated into the mainstream optimization protocol. However, it remains underexplored whether maintaining the model…
- arXiv cs.AIresearchKO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches
arXiv:2505.14777v2 Announce Type: replace-cross Abstract: The design of effective optimization algorithms for neural networks remains a fundamental challenge, and most existing methods rely on heuristic extensions of gra…
- arXiv cs.AIresearchTime-o1: Time-Series Forecasting Needs Transformed Label Alignment
arXiv:2505.17847v3 Announce Type: replace-cross Abstract: Training time-series forecasting models poses unique challenges in loss function design. Most existing approaches adopt temporal mean squared error, but this stud…
- arXiv cs.AIresearchToo Categorical to be Human: Emotion Concepts in LLMs and Humans
arXiv:2508.05880v3 Announce Type: replace-cross Abstract: Understanding human emotions is central to user-facing AI applications, safety alignment, and the simulation of human behavior. As emotional stimuli shape high-st…
- arXiv cs.AIresearchFedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models
arXiv:2508.10020v2 Announce Type: replace-cross Abstract: Enhancing LLM reasoning in federated settings is nontrivial due to stringent computational, communication, and privacy constraints, especially in healthcare, wher…
- arXiv cs.AIresearchCross-Modality Controlled Molecule Generation with Diffusion Language Model
arXiv:2508.14748v2 Announce Type: replace-cross Abstract: The increasing variety of molecular data creates a need for generative models that can flexibly incorporate heterogeneous constraints across modalities. However,…
- arXiv cs.AIresearchLHM-Humanoid: Long-Horizon Human Motion Control for Continuous Object Transport in Cluttered Scenes
arXiv:2508.16943v4 Announce Type: replace-cross Abstract: Physics-based human motion control can make a simulated character walk, sit, and manipulate objects with high physical realism. Almost always, though, this happen…
- arXiv cs.AIresearchPractical Feasibility of Gradient Inversion Attacks in Federated Learning
arXiv:2508.19819v3 Announce Type: replace-cross Abstract: Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly strong reconstructions u…
- arXiv cs.AIresearchBreaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators
arXiv:2509.03647v3 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly serve as automated evaluators, yet they suffer from "self-preference bias": a tendency to favor their own outputs over t…
- arXiv cs.AIresearchQubit-centric Transformer for Surface Code Decoding
arXiv:2510.11593v3 Announce Type: replace-cross Abstract: For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across multiple physical qubi…
- arXiv cs.AIresearchPredicting kernel regression learning curves from only raw data statistics
arXiv:2510.14878v3 Announce Type: replace-cross Abstract: We study kernel regression with common rotation-invariant kernels on real datasets including CIFAR-5m, SVHN, and ImageNet. We give a theoretical framework that pr…
- arXiv cs.AIresearchSpeak to a Protein: An Interactive Multimodal Co-Scientist
arXiv:2510.17826v2 Announce Type: replace-cross Abstract: Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and inspecting ligand comple…
- arXiv cs.AIresearchDistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment
arXiv:2510.24574v3 Announce Type: replace-cross Abstract: Training time-series forecasting models requires aligning the conditional distribution of model forecasts with that of the label sequence. The standard direct for…
- arXiv cs.AIresearchQuadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
arXiv:2511.00053v2 Announce Type: replace-cross Abstract: The design of learning objectives is central to training time-series forecasting models. Existing learning objectives such as mean squared error mostly treat each…
- arXiv cs.AIagentsStabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization
arXiv:2511.20718v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) algorithms such as PPO and GRPO are widely used to train large language models (LLMs) for multi-turn agentic tasks. However, in off-po…
- arXiv cs.AIresearchAligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
arXiv:2511.21075v4 Announce Type: replace-cross Abstract: Engineering LLMs to accelerate life sciences research requires a robust alignment with biomedical knowledge. We observe that biomedical text exhibits a fundamenta…
- arXiv cs.AIagentsMiniScope: Authorizing Agents with Least-Privilege Permissions
arXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a critical security c…
- arXiv cs.AIresearchCross-Lingual Activation Steering for Multilingual Language Models
arXiv:2601.16390v2 Announce Type: replace-cross Abstract: Large language models exhibit strong multilingual capabilities, yet significant performance gaps persist between dominant and non-dominant languages. Prior work a…
- arXiv cs.AIresearchIntersectional Fairness via Mixed-Integer Optimization
arXiv:2601.19595v2 Announce Type: replace-cross Abstract: The deployment of Artificial Intelligence in high-risk domains, such as finance and healthcare, necessitates models that are both fair and transparent. While regu…
- arXiv cs.AIresearchFast and Efficient Asynchronous Gossip Algorithm for Robust and Non-Smooth Convex Decentralized Learning
arXiv:2601.20571v3 Announce Type: replace-cross Abstract: Asynchronous primal-dual methods for decentralized non-smooth convex optimization often require each node to maintain $\mathcal{O}(d)$ auxiliary variables, where…
- arXiv cs.AIresearchRecommender system in X inadvertently profiles ideological positions of users
arXiv:2602.02624v2 Announce Type: replace-cross Abstract: Several data protection laws restrict processing that reveals political opinions, irrespective of the controller's intent. Whether recommender systems do so as a…
- arXiv cs.AIresearchSimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation
arXiv:2602.16863v3 Announce Type: replace-cross Abstract: The ability to manipulate tools significantly expands the set of tasks a robot can perform. Yet, tool manipulation represents a challenging class of dexterity, re…
- arXiv cs.AIresearchAdaptive Bidirectional Task Interaction for Joint Segmentation and Classification of Breast Ultrasound
arXiv:2603.01295v2 Announce Type: replace-cross Abstract: Joint lesion segmentation and tissue classification in breast ultrasound are usually trained with a shared encoder, so the two branches stop exchanging informatio…
- arXiv cs.AIresearchReal-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approaches
arXiv:2603.02655v2 Announce Type: replace-cross Abstract: Real-time video commentary generation provides textual descriptions of ongoing events in videos. It supports accessibility and engagement in domains such as sport…
- arXiv cs.AIresearchWorld Properties without World Models: Distributional Associations and the Interpretation of Decoding Results from Language Models
arXiv:2603.04317v2 Announce Type: replace-cross Abstract: A growing literature shows that variables can be linearly decoded from the activations of large language models (LLMs). These range from properties of the world,…
- arXiv cs.AIagentsDual-Modality Multi-Stage Adversarial Safety Training: Robustifying Multimodal Web Agents Against Cross-Modal Attacks
arXiv:2603.04364v2 Announce Type: replace-cross Abstract: Multimodal web agents that process both screenshots and accessibility trees are increasingly deployed to interact with web interfaces, yet their dual-stream archi…
- arXiv cs.AIagentsPC-Diffuser: Path-Consistent Capsule CBF Safety Filtering for Diffusion-Based Trajectory Planner
arXiv:2603.10330v3 Announce Type: replace-cross Abstract: Autonomous driving in complex traffic requires planners that generalize beyond hand-crafted rules, motivating data-driven approaches that learn behavior from expe…
- arXiv cs.AIresearchUnderstanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
arXiv:2603.16017v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly participate in morally sensitive decision-making, yet how they organize ethical frameworks across reasoning steps remain…
- arXiv cs.AIresearchFederated Mixture-of-Experts Alignment on Mobile Edge Networks under Data Heterogeneity
arXiv:2603.21276v2 Announce Type: replace-cross Abstract: The growing demand for on-device large language model (LLM) services on mobile edge devices has driven the adoption of Mixture-of-Experts (MoE) architectures, whi…
- arXiv cs.AIresearchUnbiased Reward Modeling from Implicit Feedback for LLM Alignment
arXiv:2603.23184v2 Announce Type: replace-cross Abstract: Despite the success of reinforcement learning from human feedback (RLHF), existing reward modeling methods largely rely on explicit feedback, which is costly to c…
- arXiv cs.AIresearchOne-Shot Localisation of the Global Minimum of a Noisy One-Dimensional Function: A Controlled Comparison of an Iterative Neural Minimizer, Set Transformers and Classical Estimators
arXiv:2604.03614v5 Announce Type: replace-cross Abstract: We study passive global optimisation: from twenty noisy samples of an unknown one-dimensional function, with no further queries, estimate where its global minimum…
- arXiv cs.AIresearchSinkhorn doubly stochastic attention rank decay analysis
arXiv:2604.07925v2 Announce Type: replace-cross Abstract: The self-attention mechanism is central to the success of Transformer architectures. However, standard row-stochastic attention has been shown to suffer from sign…
- arXiv cs.AIresearchCross-Cultural Value Attribution in Large Vision-Language Models
arXiv:2604.09945v3 Announce Type: replace-cross Abstract: The rapid adoption of large vision-language models (LVLMs) in recent years has been accompanied by growing fairness concerns due to their propensity to reinforce…
- arXiv cs.AIresearchLearning Visual Feature-Based World Models via Residual Latent Action
arXiv:2605.07079v2 Announce Type: replace-cross Abstract: World models predict future transitions from observations and actions. Existing works predominantly focus on image generation only. Visual feature-based world mod…
- arXiv cs.AIagentsPBT-Bench: Benchmarking AI Agents on Property-Based Testing
arXiv:2605.15229v4 Announce Type: replace-cross Abstract: Existing code benchmarks measure whether an agent can produce any test that reproduces a known bug, or whether it can produce a patch that fixes a described issue…
- arXiv cs.AIresearchVoice "Cloning" is Style Transfer
arXiv:2605.16578v4 Announce Type: replace-cross Abstract: Artificially generated speech is increasingly embedded in everyday life. Voice cloning in particular enables applications where identity preservation is important…
- arXiv cs.AIresearchStochastic Penalty-Barrier Method for Constrained Machine Learning
arXiv:2605.18618v3 Announce Type: replace-cross Abstract: Constrained Machine Learning (CML) enables fairness-aware training, physics-informed neural networks, and integration of symbolic domain knowledge into statistica…
- arXiv cs.AIagentsKadiAssistant: A conversational AI Agent for information retrieval in Kadi4Mat
arXiv:2605.18850v2 Announce Type: replace-cross Abstract: We introduce KadiAssistant, a privacy-by-design AI assistant integrated into the Kadi research data ecosystem, enabling researchers to efficiently access, aggrega…