AI news archive.
10,660 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchThe Indian Financial Automated Advice Bias (IFAAB) Dataset : Auditing Socioeconomic and Demographic Disparities in LLM-Generated Financial Advice in India
arXiv:2610.38239v1 Announce Type: cross Abstract: Large language models are increasingly used for financial guidance, yet little is known about whether their advice changes across social identities in Global South contex…
- arXiv cs.AIresearchMEV: A Multi-Event Video Dataset for Long-Take Generation
arXiv:2610.38241v1 Announce Type: cross Abstract: Current datasets for text-to-video generation are largely limited to short clips depicting a single event or coarse-grained captions. As a result, they provide limited su…
- arXiv cs.AIresearchA Tutorial on Generative Models for Music Audio
arXiv:2610.38252v1 Announce Type: cross Abstract: Music audio generation spans instrumental clips, full songs with vocals, edits of existing recordings, and systems that play alongside a musician in real time. This monog…
- arXiv cs.AIresearchCross Lingual Abstractive Summarization for Marathi
arXiv:2610.38267v1 Announce Type: cross Abstract: Text summarization is an important task for advancing natural language processing (NLP) research and applications in Indic languages. Despite progress in extractive and a…
- arXiv cs.AIresearchThe Role of Quantization in Loss Spikes
arXiv:2610.38277v1 Announce Type: cross Abstract: Loss spikes in language model pretraining can waste substantial compute and derail otherwise healthy training runs. A primary driver of these instabilities is the growth…
- arXiv cs.AIresearchLLM-PowerTrace: A Dataset of Time-Resolved GPU Power Traces for AI Compute
arXiv:2610.38315v1 Announce Type: cross Abstract: AI compute is becoming large and fast-changing electrical loads. Its impacts on data center infrastructure and power grids depend not only on total energy consumption, bu…
- arXiv cs.AIresearchExtremely Sparse-View Computed Tomography from 2D Projections via Pose-Aware Diffusion Priors
arXiv:2610.38319v1 Announce Type: cross Abstract: Extremely sparse-view computed tomography (xSV-CT) is critical when scanning time, motion, or radiation tolerance limits each scan to only a few projections. In many such…
- arXiv cs.AIresearchStatutory Article Retrieval from Arabic Judicial Narratives: Family Law and Law of Evidence in Saudi Arabia
arXiv:2610.38336v1 Announce Type: cross Abstract: Reliable legal information retrieval must ground legal reasoning in authoritative statutory sources. In Arabic judicial settings, long factual narratives must be mapped t…
- arXiv cs.AIresearchAligning Misaligned Benchmarks for Single-View Novel View Synthesis
arXiv:2610.38349v1 Announce Type: cross Abstract: While single-view novel view synthesis methods have been dramatically enhanced recently, how to quantify their performance has yet to be standardized. In this work, we de…
- arXiv cs.AIresearchSparseTokenGS: Gaussian-based Sparse-View CBCT Reconstruction via Reusable Token Pool
arXiv:2610.38360v1 Announce Type: cross Abstract: Sparse-view cone-beam computed tomography is widely used for fast, low-dose volumetric imaging and lesion localization in dentistry and image-guided interventions, but it…
- arXiv cs.AIresearchManifest-Assisted Retrieval in Artificial Intelligence Search: Evidence Gaps and a Security Evaluation
arXiv:2610.38361v1 Announce Type: cross Abstract: The external sources retained in our non-systematic audit did not isolate the incremental security or utility effect of consuming /llms.txt while ordinary retrieval remai…
- arXiv cs.AIresearchLLMs as Judges and Examinees for Medical Item Difficulty Prediction
arXiv:2610.38402v1 Announce Type: cross Abstract: Predicting medical item difficulty from item text alone remains challenging. Prior work has largely relied on linguistic features or text representations derived from gen…
- arXiv cs.AIresearchSpaceAct: Benchmarking 3D Spatial and Temporal Reasoning via Closed-Loop Action and Active Perception
arXiv:2610.38405v1 Announce Type: cross Abstract: To solve problems in 3D space rather than merely describe images, multimodal large language models (MLLMs) need 3D spatiotemporal reasoning: reconstructing 3D geometry fr…
- arXiv cs.AIresearchDecisionUnlearn-Bench: Unlearning Probabilistic Decisions under Changing Schemas
arXiv:2610.38431v1 Announce Type: cross Abstract: Machine unlearning aims to reproduce the behavior of a model trained without designated data. For probabilistic decision models, this target also depends on the candidate…
- arXiv cs.AIresearchSaiVLA-JEPA: Evaluating Future Latent Prediction in JEPA-Conditioned VLA Control
arXiv:2610.38508v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) learn to predict representations rather than pixels, offering a compact way to model how visual scenes evolve. We ask whe…
- arXiv cs.AIresearchAtomSteer: Test-Time Constraint Steering for Atomistic Generative Models
arXiv:2610.38517v1 Announce Type: cross Abstract: Diffusion and flow matching models offer scalable approaches to generating crystalline materials, molecular conformers, and protein-ligand complexes. However, satisfying…
- arXiv cs.AIresearchDo Audio LLMs HEAR Pain? Tracing Acoustic Evidence from Speech to Language Reasoning
arXiv:2610.38570v1 Announce Type: cross Abstract: Large audio language models (LALMs) can process speech directly, but it remains unclear how well they use the non-lexical acoustic information that speech carries. We stu…
- arXiv cs.AIresearchEpisodic looking - using reinforcement learning to bias perception enhances few-shot and continual learning with protection from forgetting
arXiv:2610.38577v1 Announce Type: cross Abstract: There is a fundamental contradiction between the desire for models that can generalize, and models that can continuously adapt to recent input with changing statistics. T…
- arXiv cs.AIresearchOn-Policy Self-Distillation with Teacher Evolution
arXiv:2610.38637v1 Announce Type: cross Abstract: On-Policy Self-Distillation (OPSD), which aligns a student model's token-level distribution with that of its self-teacher prompted by privileged context, has emerged as a…
- arXiv cs.AIresearchEnhanced image forensics through partial C2PA-based provenance information
arXiv:2610.38639v1 Announce Type: cross Abstract: Cryptographically verifiable C2PA-based Content Credentials (CCs) can be attached to freshly acquired or generated digital images but also to already existing ones with n…
- arXiv cs.AIresearchWhen AI performs, what remains? An integrative review of generative AI and cognitive capital in individuals and organizations
arXiv:2610.38647v1 Announce Type: cross Abstract: Generative artificial intelligence is rapidly entering knowledge work, and its short-term productivity benefits are increasingly documented. Less is known about what happ…
- arXiv cs.AIresearchInformation-Theoretic Reliability--Safety Bounds and Finite-Alignment Dynamics in AI Knowledge Distillation
arXiv:2610.38651v1 Announce Type: cross Abstract: The reliability and safety of artificial intelligence (AI), together with their transfer and evolution through knowledge distillation, have attracted growing attention. W…
- arXiv cs.AIresearchExplore Where It Matters: Targeted Exploration for Efficient Rover Adaptation
arXiv:2610.38657v1 Announce Type: cross Abstract: Future planetary rovers will traverse steep, deformable terrain where slip, sinkage, and terrain deformation can threaten mobility. Although simulation can capture some w…
- arXiv cs.AIresearchGeometry Matters in Packed 3D Attention
arXiv:2610.38694v1 Announce Type: cross Abstract: Packing a 3D volume into a token sequence is not merely long-sequence modeling. Once the volume is packed, sequence order no longer encodes the geometry of the sample---s…
- arXiv cs.AIresearchSatOps-Decision: Low-Latency Discriminative Decisions for Onboard Satellite Communication Operations
arXiv:2610.38697v1 Announce Type: cross Abstract: We propose SatOps-Decision, a method for low-latency decisions in satellite communication operations. To the best of our knowledge, it is the first application of Jev-sty…
- arXiv cs.AIresearchLatent Decision Flow Rewards for Clinical Guideline Reasoning
arXiv:2610.38709v1 Announce Type: cross Abstract: Clinical practice guidelines encode evidence-based recommendations as conditional decision flows, which makes them a natural source of process supervision for training re…
- arXiv cs.AIresearchLearning Scientific Trajectories to Predict Future Biomedical Discoveries
arXiv:2610.38719v1 Announce Type: cross Abstract: AI co-scientists have expanded the use of large language models for generating scientific hypotheses and guiding experimental investigation. Here we investigate whether t…
- arXiv cs.AIresearchinkGround: Benchmarking Fine-grained Visual Grounding Capabilities of Vision-Language Models for Cursive Handwriting in the Wild
arXiv:2610.38720v1 Announce Type: cross Abstract: Human handwriting is produced as an ordered sequence of pen movements, but an offline image keeps only the final ink. Handwriting trajectory recovery aims to restore the…
- arXiv cs.AIresearchCopyLoop: Fast Looped Transformer Decoding via Context Copying and Shallow Screening
arXiv:2610.38822v1 Announce Type: cross Abstract: Looped Transformers increase computational capacity through the repeated application of shared blocks, but their recurrent depth makes conventional full-depth decoding ex…
- arXiv cs.AIresearchEvaluating Visual Realism of AI-Generated Videos with Eye Tracking
arXiv:2610.38825v1 Announce Type: cross Abstract: Human evaluation of AI-generated videos has so far relied on explicit human feedback, such as judgments or ratings. While these signals capture the conclusions viewers re…
- arXiv cs.AIresearchDiscovering Jailbreaks via Curriculum of Models
arXiv:2610.38833v1 Announce Type: cross Abstract: Automated jailbreak discovery aims to find prompts that elicit prohibited behaviors from safety-trained language models, helping developers identify vulnerabilities befor…
- arXiv cs.AIresearchFlipJev: Fast Black-Box Red Teaming Finds Universal Adversarial Suffixes for Typed Decision Models
arXiv:2610.38895v1 Announce Type: cross Abstract: Typed decision models are an emerging class of language models that make decisions instead of generating free-text responses. They answer in a single fast and cheap query…
- arXiv cs.AIresearchInterventional Training Reduces Causal Bypass in In-Context Introspection
arXiv:2610.38911v1 Announce Type: cross Abstract: Introspection, the ability of a system to access and reason about its internal signals, is crucial for language model (LM) self-consistency and scalable interpretability.…
- arXiv cs.AIresearchLev-3B: A Data Recipe for Compact Probabilistic Log Decision Models
arXiv:2610.38915v1 Announce Type: cross Abstract: Many log-analysis tasks involve choosing among known options, such as detecting anomalous sessions or identifying attack techniques, and benefit from calibrated probabili…
- arXiv cs.AIresearchTrussTutor-Bench: Benchmarking large language models on solution accuracy, sycophancy, and error detection in statics
arXiv:2610.38917v1 Announce Type: cross Abstract: Large language models (LLMs) have rapidly become a default source of help for students in science and engineering courses. In foundational engineering mechanics courses s…
- arXiv cs.AIresearchTableTune: Measured, Self-Correcting Draft-Length Tables for Dynamic Speculative Decoding
arXiv:2610.38968v1 Announce Type: cross Abstract: Speculative decoding speeds up large language model (LLM) serving only while the GPU has spare compute, so the best draft length, the number of tokens a small drafter gue…
- arXiv cs.AIresearchWhy Speculative Decoding Works Better Than Predicted on Sparse MoE Models
arXiv:2610.38981v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates autoregressive inference by leveraging the memory bound nature of decoding, verifying multiple draft tokens in a single forward pass…
- arXiv cs.AIresearchBenchmarking Graph Neural Networks for AC Power Flow: The Role of Inductive Biases and Physical Constraints
arXiv:2610.38985v1 Announce Type: cross Abstract: Fast and accurate models for AC power flow (ACPF) are increasingly important as modern electrical grids require more frequent system analyses. Graph neural networks (GNNs…
- arXiv cs.AIresearchRethinking GFlowNet Training: Negative Reinforce Dynamics
arXiv:2610.38994v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) are models that learn to sample discrete objects proportional to a target reward. They are trained by minimizing balance errors over…
- arXiv cs.AIresearchAssessing feature scorer results on high-dimensional datasets with t-SNE
arXiv:2610.39009v1 Announce Type: cross Abstract: While vast literature on high-dimensional data visualization is available, there are not many works regarding the visualization of feature scorers and their results. Feat…
- arXiv cs.AIresearchImplicit Reasoning in Transformers: Bridging the Compositionality Gap in GPT-2-like Models
arXiv:2610.39016v1 Announce Type: cross Abstract: Compositional generalization remains a persistent limitation of transformer language models: even when a model learns to combine known facts correctly in-distribution (ID…
- arXiv cs.AIresearchDistilling the Shape of Uncertainty: What On-Policy Distillation Learns and How to Predict It
arXiv:2610.39020v1 Announce Type: cross Abstract: On-policy distillation (OPD) is increasingly adopted in the post-training of large language models. However, a stronger teacher may fail to improve the student. Prior wor…
- arXiv cs.AIresearchRepresentation Complexity Along Learning Trajectories: Trading Width for Precision and Time
arXiv:2610.39027v1 Announce Type: cross Abstract: What computational role does overparameterisation play during learning? Information-plane analyses suggest that neural networks can traverse representations substantially…
- arXiv cs.AIresearchReinforcement Learning for the Game of Balatro: A Fast Simulator and Two-Policy Training Approach
arXiv:2610.39049v1 Announce Type: cross Abstract: Balatro, a 2024 roguelike deckbuilder, presents three difficulties that have historically derailed reinforcement learning methods: a 3,000-action state-dependent action s…
- arXiv cs.AIresearchWhen Does Closed-Loop Curriculum Adaptation Help GRPO? An Analysis on Countdown
arXiv:2610.39056v1 Announce Type: cross Abstract: Reinforcement fine-tuning has become an effective post-training paradigm for improving the reasoning ability of large language models, but it remains sample-inefficient w…
- arXiv cs.AIresearchTactus: Tactile & Pose Sensing Glove for Natural Dexterity Data Collection
arXiv:2610.39076v1 Announce Type: cross Abstract: Collecting naturalistic human manipulation demonstrations with accurate contact force and hand pose is essential for robot dexterous manipulation policy and foundational…
- arXiv cs.AIresearchGenerating Critic-Guided Synthetic Experience in Latent World Models
arXiv:2610.39100v1 Announce Type: cross Abstract: Learning from offline datasets is limited in scalability, as collecting new experience is often costly or unsafe in the real world. World models offer an alternative way…
- arXiv cs.AIresearchFrom Local Recovery to Unified Generation: Discovering Triple Set in Knowledge Graphs via Observation-Anchored Latent Diffusion
arXiv:2610.39114v1 Announce Type: cross Abstract: Triple set prediction (TSP) is to recover missing relational triples in a knowledge graph by predicting the triple set instead of isolated links. Existing approaches pred…
- arXiv cs.AIresearchPRISM: Personalized Item Representations in User History
arXiv:2610.39175v1 Announce Type: cross Abstract: Sequential recommenders typically construct history inputs from item identifiers or content features using an embedding map shared across users. The same item therefore y…
- arXiv cs.AIresearchWhere Position Matters: Profiling-Guided Layer-Wise RoPE Allocation in Transformers
arXiv:2610.39223v1 Announce Type: cross Abstract: Rotary Position Embedding (RoPE) typically uses uniform coverage across Transformer layers despite heterogeneous positional requirements. Phase-off interventions reveal n…