AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchADATEX4D: adaptive texture capacity allocation for 4D gaussian splatting
arXiv:2609.29963v2 Announce Type: replace-cross Abstract: Textured Gaussians improve local appearance capacity, but assigning the same texture resolution to every primitive wastes storage on low-detail or weakly visible…
- arXiv cs.AIresearchLearning Better Reasoning for Generative Recommendation with Semantic IDs
arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user's interaction histor…
- arXiv cs.AIresearchFrom Interests to Semantic IDs: Retrieval-Grounded Credit Assignment for Generative Recommendation
arXiv:2609.29983v1 Announce Type: cross Abstract: Semantic IDs (SIDs) encode each catalog item as a short token sequence, enabling generative recommenders to predict the next item autoregressively. Reasoning-enhanced var…
- arXiv cs.AIresearchGHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS
arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving a headline score doe…
- arXiv cs.AIresearchAutomated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation
arXiv:2609.30009v1 Announce Type: cross Abstract: Financial institutions operate under dense, frequently amended rulebooks, and answering a compliance question correctly requires not only fluency but verifiable grounding…
- arXiv cs.AIresearchLow-Cost Assays for Measuring Model Behavior Across Vendors and Releases
arXiv:2609.30012v1 Announce Type: cross Abstract: Language models advise people, keep them company, and write software while they sleep. Measuring what they do is hard: behavior has to be sampled repeatedly across models…
- arXiv cs.AIresearchCanopy: Exploiting Piecewise Smooth Tree Priors for Multi-Fidelity Bandits
arXiv:2609.30017v1 Announce Type: cross Abstract: Many LLM inference problems, including model routing, prefix-cache management, prompt trimming, and test-time search, can be viewed as optimization over a tree. This stru…
- arXiv cs.AIresearchCan Labor Markets Function in the Age of AI? The Evaluation Bottleneck in Hiring
arXiv:2609.30058v1 Announce Type: cross Abstract: AI-assisted job-search tools have become increasingly popular by making it easier to find and apply to jobs. But by making it easier for applicants to generate and tailor…
- arXiv cs.AIresearchHow Reproducible Are Evaluation Conclusions? A Self-Audit of LLM-Inferred Prompt Structure
arXiv:2609.30074v1 Announce Type: cross Abstract: Evaluations of LLM systems routinely average over small prompt sets and report models as a ranked table. We ask how much confidence such a table deserves, using LLM-based…
- arXiv cs.AIresearchReachability-Based Formal Verification of Graph Neural Networks with Node and Edge Features
arXiv:2609.30079v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have become a prominent approach for developing fast, topology-aware surrogates in electric power systems, supporting tasks such as power flo…
- arXiv cs.AIresearchAT-SKM-Net: An Accelerated Trainable Sampling Kaczmarz-Motzkin Framework for Linear Hard-Constraint Feasibility on Dynamic Graphs
arXiv:2609.30088v1 Announce Type: cross Abstract: Graph-structured optimization with linear constraints is fundamental to critical infrastructure but faces scalability limits due to massive strict hard constraints and hi…
- arXiv cs.AIresearchAccelerating Video Diffusion via Training-Free Trajectory Routing
arXiv:2609.30096v1 Announce Type: cross Abstract: Video diffusion is computationally expensive, as it requires executing a large model across many denoising steps. Even with step-distillation, inference remains expensive…
- arXiv cs.AIresearchR-DEIM Net: An Efficient Rationale-Augmented Dual-Expert Interaction Model for Paraphrase Detection
arXiv:2609.30100v2 Announce Type: replace-cross Abstract: Recent advances in paraphrase detection reveal a fundamental trade-off: large language models achieve high accuracy but require high computation, while efficient…
- arXiv cs.AIresearchDoes a model's stated reason for rejecting a candidate do any work?
arXiv:2609.30151v1 Announce Type: cross Abstract: Asked to choose between candidates and explain the choice, a language model often rejects a rival by naming a fact its profile lacks: no director, no date of death. That…
- arXiv cs.AIresearchUnderwater C3-JEPA: An Object-Centric Cross-View World Model for ROV Salvage
arXiv:2609.30214v1 Announce Type: cross Abstract: We present Underwater C$^{3}$-JEPA (cross-view, control-conditioned, context-extended), an object-centric multi-view predictive world model for near-field heavy-load unde…
- arXiv cs.AIresearchMinimally Invasive Steering of Language Models
arXiv:2609.30218v1 Announce Type: cross Abstract: Pre-logit steering adapts a frozen language model to a test-time reward by adding vectors to its final hidden states. Unregularized reward optimization can substantially…
- arXiv cs.AIresearchRequirement-Bound Verified Commissioning: A Frozen Four-Billion-Parameter Local Model as a Candidate Generator under an External Acceptance Layer with Verification and Release Authority
arXiv:2609.30219v1 Announce Type: cross Abstract: An acceptance protocol is developed for sensor-coordinate and polarity binding in mechatronic commissioning. Candidate generation is separated from release authority. Req…
- arXiv cs.AIresearchTrackEverything: Long Horizon Dense Tracking via De-Duplicating 3D Scene Representations
arXiv:2609.30222v1 Announce Type: cross Abstract: Existing point tracking models face a fundamental tradeoff: they can either track a sparse set of query points over long horizons, or track all points across only short c…
- arXiv cs.AIresearchPoEM: Predicting RL Outcomes from Existing Policies
arXiv:2609.30226v1 Announce Type: cross Abstract: Foundation models are post-trained with reinforcement learning (RL) to maximize specific rewards, such as human alignment, correctness, or instruction following. This pos…
- arXiv cs.AIresearchTo Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech
arXiv:2609.30227v1 Announce Type: cross Abstract: Online misinformation increasingly appears in spoken formats such as news clips, podcasts, interviews, political speeches, and social media videos, creating a need for fa…
- arXiv cs.AIresearchRolling-WAM: World Action Models with Rolling Imagination
arXiv:2609.30247v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) couple action generation with future visual prediction for robotic manipulation. However, completing the joint video-action denoising p…
- arXiv cs.AIresearchGenerating Interesting Scientific Ideas using Knowledge Graphs and LLMs: Evaluations with 100 Research Group Leaders
arXiv:2405.17044v4 Announce Type: replace Abstract: The rapid growth of scientific literature makes it increasingly challenging for researchers to identify novel and impactful ideas, especially across disciplines. Modern…
- arXiv cs.AIresearchUnraveling the cognitive patterns of Large Language Models through module communities
arXiv:2508.18192v2 Announce Type: replace Abstract: Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging from scientific dis…
- arXiv cs.AIresearchLOGIC: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration
arXiv:2601.15397v4 Announce Type: replace Abstract: Recognizing entity phrases remains a critical challenge for speech large language models. Existing prompting methods lack an explicit decoding-time biasing weight, limi…
- arXiv cs.AIresearchSafety Under Scaffolding: How Evaluation Conditions Shape Measured Safety
arXiv:2603.10044v4 Announce Type: replace Abstract: Safety benchmarks usually test "bare" models that receive prompts and output responses, but real-world deployments "wrap" those models in complex scaffolds. How much do…
- arXiv cs.AIresearchIatroBench: A Pre-Registered Benchmark of Clinical Omission in Language Models
arXiv:2604.07709v5 Announce Type: replace Abstract: A strongly safety-trained model will provide a doctor with a benzodiazepine taper schedule, but not a patient who asks for one. The model knows the information, but how…
- arXiv cs.AIresearchBEHAVE: Real-Time Modeling of Human Systems as Observable Complex Dynamical Systems and Operational Objects for Physical AI
arXiv:2605.12730v2 Announce Type: replace Abstract: A robot can track every person and still fail to see the system those people form. BEHAVE treats an interacting human group as a complex dynamical system: a HumanSystem…
- arXiv cs.AIresearchPlanning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners
arXiv:2606.01810v5 Announce Type: replace Abstract: Current benchmarks for embodied vision-language planning inadvertently favor linguistic next-token prediction over physically grounded next-state reasoning. This reward…
- arXiv cs.AIresearchAnswering Path Queries under Linear and Guarded Existential Rules
arXiv:2607.22636v2 Announce Type: replace Abstract: Ontology-mediated query answering is concerned with the problem of answering queries over knowledge bases consisting of a database instance and an ontology. While most…
- arXiv cs.AIresearchChart-Supported or Model-Supplied? Examining MLLM-Generated Claims for Accessible Visualization
arXiv:2607.25021v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can connect visualization patterns to external causes, consequences, and domain knowledge, but the evidential basis of these in…
- arXiv cs.AIresearchTRACE: Trajectory Aware Reasoning for Multi-Turn Adversarial Conversation Evaluation
arXiv:2608.15594v2 Announce Type: replace Abstract: Multi-turn jailbreak attacks have emerged as a critical safety threat to LLMs, as harmful objectives are decomposed across a sequence of apparently benign turns to bypa…
- arXiv cs.AIresearchDCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution
arXiv:2401.08875v3 Announce Type: replace-cross Abstract: Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While recent studies incorpo…
- arXiv cs.AIresearchELiSe: Efficient Learning of Sequences in Structured Recurrent Networks
arXiv:2402.16763v4 Announce Type: replace-cross Abstract: Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks, memories of past a…
- arXiv cs.AIresearchBand-Attention Modulation Network for Robust Face Forgery Detection
arXiv:2404.06022v3 Announce Type: replace-cross Abstract: Face forgery detection faces critical challenges in generalizing to unseen manipulation techniques and remaining robust under image compression, which often obscu…
- arXiv cs.AIresearchDeep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
arXiv:2405.18929v3 Announce Type: replace-cross Abstract: Semi-supervised anomaly detection, which aims to improve the anomaly detection performance by using a small amount of labeled anomaly data in addition to unlabele…
- arXiv cs.AIresearchHow Do Users Negotiate Harmful Value Conflicts with AI Companions? A Study with Minion, a Technology Probe for In-Situ Human-AI Conflict Response
arXiv:2411.07042v3 Announce Type: replace-cross Abstract: AI companions increasingly sustain long-term, emotionally engaging relationships but can also make discriminatory remarks or exert control, leaving users to manag…
- arXiv cs.AIresearchFoundations of Large Language Models
arXiv:2501.09223v4 Announce Type: replace-cross Abstract: This is a book about large language models. As indicated by the title, it primarily focuses on foundational concepts rather than comprehensive coverage of all cut…
- arXiv cs.AIresearchMultimodal AI predicts clinical outcomes of drug combinations from preclinical data
arXiv:2503.02781v3 Announce Type: replace-cross Abstract: Predicting clinical outcomes from preclinical data is essential for selecting safe and effective drug combinations and for reducing late-stage failures. AI models…
- arXiv cs.AIresearchSearch-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmap
arXiv:2505.19625v4 Announce Type: replace-cross Abstract: Search-based software engineering (SBSE), which integrates metaheuristic search techniques with software engineering, has been an active area of research for abou…
- arXiv cs.AIresearchConversational DNA: A Visual Language and Interactive Atlas of Human and AI Dialogue
arXiv:2508.07520v2 Announce Type: replace-cross Abstract: What makes a conversation hold together when its participants speak across one another? Topic maps offer one view, but they leave the relationships between contri…
- arXiv cs.AIresearchCross-Task Generalization in Handwriting-Based Alzheimer's Screening via Vision Language Adaptation
arXiv:2511.05841v2 Announce Type: replace-cross Abstract: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder for which early detection is critical. Handwriting, which can be disrupted by subtle motor and…
- arXiv cs.AIresearchSPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions
arXiv:2512.14277v2 Announce Type: replace-cross Abstract: The advent of large language models is contributing to the emergence of novel approaches that promise to better tackle the challenge of generating structured quer…
- arXiv cs.AIresearchTIDE: Temporal Incremental Draft Engine for Self-Improving LLM Inference
arXiv:2602.05145v2 Announce Type: replace-cross Abstract: Speculative decoding can substantially accelerate LLM inference, but realizing its benefits in practice is challenging due to evolving workloads. We present TIDE…
- arXiv cs.AIresearchNear-Oracle KV Selection via Pre-hoc Sparsity for Long-Context Inference
arXiv:2602.08329v2 Announce Type: replace-cross Abstract: A core bottleneck in large language model (LLM) inference is the cost of attending over the ever-growing key-value (KV) cache. Although near-oracle top-k KV selec…
- arXiv cs.AIresearchTabSieve: Explicit In-Table Evidence Selection for Tabular Prediction
arXiv:2602.11700v2 Announce Type: replace-cross Abstract: Tabular prediction can benefit from in-table rows as few-shot evidence, yet existing tabular models typically perform instance-wise inference and LLM-based prompt…
- arXiv cs.AIresearchVLANeXt Family: A Systematic Study of VLA Models from Core Recipes to Emerging Paradigms
arXiv:2602.18532v5 Announce Type: replace-cross Abstract: Following the rise of large foundation models, Vision-Language-Action models (VLAs) emerged, leveraging strong visual and language understanding from Vision-Langu…
- arXiv cs.AIresearchSHINE: Sequential Hierarchical Integration Network for EEG and MEG
arXiv:2602.23960v2 Announce Type: replace-cross Abstract: How natural speech is represented in the brain constitutes a major challenge for cognitive neuroscience. Reconstructing the speech envelope and Mel spectrogram fr…
- arXiv cs.AIresearchLearning Causal Structure of Time Series using Best Order Score Search
arXiv:2603.05370v2 Announce Type: replace-cross Abstract: Causal structure learning from observational data is central to many scientific and policy domains, but the time series setting common to many disciplines poses s…
- arXiv cs.AIresearchLiveMathematicianBench: A Live Benchmark for Research-Level Mathematical Reasoning with Proof Sketches
arXiv:2604.01754v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a hallmark of human intelligence, and whether large language models (LLMs) can meaningfully perform it remains a central question in art…
- arXiv cs.AIresearchFrontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation
arXiv:2605.04135v4 Announce Type: replace-cross Abstract: LLM evaluations in applied domains tend to reflect models that were already outclassed at time of publication. We observe a publication elicitation gap: the dista…