AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchPrivacy-preserving inference on hosted models: a learned input-embedding transform for frozen Qwen3.8-27B
arXiv:2610.27817v1 Announce Type: new Abstract: Every prompt sent to a hosted language model is readable by whoever runs it. We study whether the prompt can remain on the client while the host receives transformed vector…
- arXiv cs.AIresearchPhysical Operating-Condition-Guided Vision-Language Matching for Cavitation Diagnosis in Industrial Pipeline Systems
arXiv:2610.27860v1 Announce Type: new Abstract: Cavitation diagnosis in industrial pipeline systems is challenging because acoustic responses vary substantially with operating conditions, while similar time-frequency pat…
- arXiv cs.AIresearchAutomatic Differentiation with Constraints in Forward and Inverse Problems
arXiv:2610.27888v2 Announce Type: replace Abstract: Approximate solutions of partial differential equations (PDEs) on unstructured grids can be represented on a graph. Numerical optimization involving stiff evolutionary…
- arXiv cs.AIresearchStaged Continual Adaptation of Multimodal Foundation Models for Japanese Financial Documents
arXiv:2610.27904v1 Announce Type: new Abstract: Staged post-training of multimodal foundation models chains vision-language alignment, reasoning distillation, and domain tuning, yet how each phase trades capabilities aga…
- arXiv cs.AIresearchACE-Compression: An Ability-Centric Evaluation of Compressed Large Language Models
arXiv:2610.27913v1 Announce Type: new Abstract: Model compression makes large language models deployable, but today's evaluation tells an incomplete story. Standard practice measures retained task performance and stops t…
- arXiv cs.AIresearchQuantum-JEPA: Quantum Born Priors for Latent-Action JEPA World Models
arXiv:2610.27921v1 Announce Type: new Abstract: A single observation can admit several plausible futures, making uncertainty an essential part of world modelling. However, quantum generative models remain underexplored f…
- arXiv cs.AIresearchFrom Comparison to Selection: Enhancing Cross-Scale Generalization of Pointer Networks Trained with Reinforcement Learning for Capacitated Vehicle Routing Problem
arXiv:2610.27936v3 Announce Type: replace Abstract: Vehicle routing in delivery and logistics remains challenging as the number of clients varies. Classical approaches based on mixed-integer programming and heuristics ca…
- arXiv cs.AIresearchHypTI: Hyperbolic Geometry-Aware Multimodal Feature Fusion Framework for Dementia Detection Based on Tabular-Image Data
arXiv:2610.27941v1 Announce Type: new Abstract: AI-assisted dementia detection usually requires multimodal fusion of diverse data, such as clinical tabular assessments and neuroimaging data. However, most existing approa…
- arXiv cs.AIresearchBuilding Telecom Language Models with RSOD: Domain Data, Specialist Post-Training, Memory-Conscious Distillation, and Networking Evaluation
arXiv:2610.27993v1 Announce Type: new Abstract: Telecom language models must combine broad networking knowledge with specialist behavior across routing, broadband services, access technologies, and operational diagnostic…
- arXiv cs.AIresearchDancing Diffusion: Learning Continuous Programs for Image Generation and Editing
arXiv:2610.28003v2 Announce Type: replace Abstract: Diffusion models generate samples through a multi-step denoising trajectory, yet condition every step on the same instruction, so the trajectory cannot be addressed at…
- arXiv cs.AIresearchTrajEvolve: Trajectory Evolution for Reinforcement Learning with Hindsight Credit Assignment
arXiv:2610.28060v1 Announce Type: new Abstract: The Reinforcement Learning (RL) paradigm has achieved remarkable success in enhancing the reasoning capabilities of Large Language Models (LLMs). However, when applied to l…
- arXiv cs.AIresearchSlot-JEPA: Object-Structured Prediction Interfaces for Latent World Models
arXiv:2610.28074v1 Announce Type: new Abstract: As a prototypical latent world model, Joint-Embedding Predictive Architectures (JEPAs) provide strong semantic representations. However, dense patch representations expose…
- arXiv cs.AIresearchIECG: Weakly-Supervised Interpretability-Enhancing Foundation Model for Electrocardiogram
arXiv:2610.28083v1 Announce Type: new Abstract: Electrocardiography (ECG) is a cornerstone of cardiac diagnosis, yet most machine learning methods for ECG analysis lack interpretability, limiting their clinical adoption.…
- arXiv cs.AIresearchInsightRAG: Aggregating Distributed Scholarly Judgments for Scientific Survey Generation
arXiv:2610.28085v1 Announce Type: new Abstract: The rapid growth of scientific literature makes survey writing increasingly challenging, motivating automatic survey generation. Yet, existing systems must search an open s…
- arXiv cs.AIresearchPolyscene: Scenario Planning as Diversity Planning
arXiv:2610.28102v1 Announce Type: new Abstract: Scenario planning is a foresight practice in which analysts construct a small set of plausible futures and prepare an organisation for each. Each scenario is a narrative th…
- arXiv cs.AIresearchA Semi-Analytical Inference Framework for Structural Causal Models
arXiv:2610.28103v1 Announce Type: new Abstract: Structural Causal Models (SCMs) provide a principled framework for observational, interventional, and counterfactual reasoning, all of which rely on probabilistic inference…
- arXiv cs.AIresearchRobust Representation Learning for Spiking Neural Networks based on Conditional Information Bottleneck
arXiv:2610.28110v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) have shown great potential for low-power neuromorphic computing due to their event-driven processing and spatiotemporal sparsity, but they re…
- arXiv cs.AIresearchIs Sycophancy a Form of In-Context Updating?
arXiv:2610.28325v1 Announce Type: new Abstract: Factual sycophancy, a language model's deference to a user's false beliefs, is usually understood as a bid for the user's approval at the expense of truthfulness. We argue…
- arXiv cs.AIresearchRACE: RoPE-Aligned Attention Compression Based on Query-Key Activation Energies
arXiv:2610.28385v1 Announce Type: new Abstract: Head-dimension compression can reduce the memory required by the key-value (KV) cache, but existing methods often reconstruct full-dimensional representations during infere…
- arXiv cs.AIresearchDIVE: Benchmarking Full-Duplex Interaction with Visual Engagement in Continuous Streams
arXiv:2610.28405v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have substantially improved spoken interaction and video understanding. Existing online and streaming benchmarks…
- arXiv cs.AIresearchStratified Sparse Attention: Reducing the Sparse-to-Dense Gap at Extreme Sparsity
arXiv:2610.28441v1 Announce Type: new Abstract: Large Language Model inference over long contexts is increasingly bottlenecked by the cost of attending to a growing Key-Value (KV) cache. Sparse attention reduces this cos…
- arXiv cs.AIresearchBeyond Trajectory Statistics: Community-Consistent Human Mobility Generation via Evolving User-Location Graphs
arXiv:2610.28467v2 Announce Type: replace Abstract: Human mobility data are fundamental to Web-based location services and broader urban applications, and mobility generation provides synthetic trajectories when real dat…
- arXiv cs.AIresearchExploring Temporal Context-Aware Physical Grounding in Latent World Models
arXiv:2610.28483v1 Announce Type: new Abstract: Learning latent dynamics is fundamental to building action-conditioned world models for planning. Among existing families, Joint Embedding Predictive Architectures (JEPAs)…
- arXiv cs.AIresearchDecisionPivot: A Diagnostic Benchmark for Decision Models in LLM Systems
arXiv:2610.28522v1 Announce Type: new Abstract: Decision models support routing, guardrails, and output verification in LLM systems. However, item accuracy alone cannot establish whether models make correct decisions acr…
- arXiv cs.AIresearchBeyond 4 bits: Data-Centric Post-training Quantization and Recovery
arXiv:2610.28537v1 Announce Type: new Abstract: Post-training quantization (PTQ) compresses the weights of a trained model with limited compute and data. Down to 4 bits it is near-lossless, but at 2 bits scalar PTQ confi…
- arXiv cs.AIresearchHumans Correct Their Judgments Through Debate, but Weaker AI Models Do Not
arXiv:2610.28539v1 Announce Type: new Abstract: How can we effectively oversee AI systems that surpass human intelligence? AI Safety via Debate proposes that two AI systems argue opposing positions and a judge, either a…
- arXiv cs.AIresearchOptScientist: Automated Discovery of Optimization Laws
arXiv:2610.28562v1 Announce Type: new Abstract: Many scientific phenomena are best understood as outcomes of underlying optimization problems, yet automated scientific discovery has largely focused on recovering equation…
- arXiv cs.AIresearchEvolving Semantic Indexes for Generative Retrieval
arXiv:2610.28568v1 Announce Type: new Abstract: Generative retrieval (GR) casts search and recommendation as autoregressive generation of discrete semantic identifiers (SIDs). SID design largely determines GR quality, bu…
- arXiv cs.AIresearchBeyond the Sequentiality Bottleneck: A Hybrid Diffusion-Autoregressive Framework for Efficient Multimodal Reasoning
arXiv:2610.28584v1 Announce Type: new Abstract: Autoregressive models (ARMs) face a "Sequentiality Bottleneck" in reasoning, while diffusion language models (DLMs) offer parallelism but lack semantic coherence. To addres…
- arXiv cs.AIresearchWhat Do RTL Repair Benchmarks Actually Measure?
arXiv:2610.28595v1 Announce Type: new Abstract: RTL repair benchmarks should measure whether a model can fix broken RTL given a specification. To this end, we construct and hash-bind RTLRepairDataset, 5,784 (broken, fixe…
- arXiv cs.AIresearchValue-Rich, Differently Organized: Measuring Value Expression and Organization in AI-Generated Debates
arXiv:2610.28604v1 Announce Type: new Abstract: Current evaluation of LLM-generated debate largely focuses on argumentative quality, leaving the value structure of generated arguments underexamined. We introduce a diagno…
- arXiv cs.AIresearchAdaptive Multi-Token Prediction: How far should we go?
arXiv:2610.28619v1 Announce Type: new Abstract: Multi-token prediction (MTP) can accelerate language-model decoding by drafting several tokens and verifying them in a single target-model pass. However, the best speculati…
- arXiv cs.AIresearchFine-Tuning Small Language Models for Reliable VASP INCAR Generation
arXiv:2608.05387v1 Announce Type: cross Abstract: Language models can prepare VASP INCAR files from natural-language requests, but so far only large proprietary cloud models come close to handling the tightly coupled, ph…
- arXiv cs.AIresearchDisentangling Depression from Cognitive Decline in Elderly Speech Using Concurrent Clinical Assessments
arXiv:2610.26890v1 Announce Type: cross Abstract: Detecting depression from speech in elderly patients with mild cognitive impairment (MCI) is complicated by overlapping acoustic effects of cognitive decline. Without dis…
- arXiv cs.AIresearchPW-Pruning: Phase-Aware Expert Selection for Speech-Centric Omni-Modal Models
arXiv:2610.26891v1 Announce Type: cross Abstract: Sparse routing reduces per-token computation but leaves the full expert bank resident in memory. We study expert pruning for speech-centric omni-modal models, where pooli…
- arXiv cs.AIresearchMOSS: A Production Framework for Monitoring and Diagnosing Semantic Failures in Search and Recommendation Systems
arXiv:2610.26902v1 Announce Type: cross Abstract: Detecting semantic failures in production recommendation and search systems is hard: behavioral metrics lag by days, manual review does not scale, and most LLM evaluation…
- arXiv cs.AIresearchUncertainty Gates the Gradient: Adaptive Updates for Generalized Few-Shot 3D Segmentation
arXiv:2610.26909v1 Announce Type: cross Abstract: In generalized few-shot 3D point cloud segmentation, support annotations are often compromised by sparsity and occlusion. Blindly adapting to such low quality samples ris…
- arXiv cs.AIresearchSteerable Pluralistic Policy Alignment from Anonymized Crowd Feedback
arXiv:2610.26914v1 Announce Type: cross Abstract: Pluralistic alignment requires AI systems to learn from diverse populations whose preferences may reflect heterogeneous or even conflicting objectives, and to personalize…
- arXiv cs.AIresearchEnhancing analytical photon transport in turbid media through physics-guided neural network corrections
arXiv:2610.26917v1 Announce Type: cross Abstract: Analytical methods provide rapid and computationally efficient predictions of light transport in turbid media, making them attractive for real-time and inverse applicatio…
- arXiv cs.AIresearchMultilingual Brain Decoding Reveals Shared Cortical Semantic Geometry
arXiv:2610.26927v1 Announce Type: cross Abstract: Human languages differ markedly in lexical and syntactic form yet can convey similar semantic content. The neural basis of this cross-language semantic commonality remain…
- arXiv cs.AIresearchGRaSP: Latency-Aware Optimization for Geo-Distributed Retrieval-Augmented Generation
arXiv:2610.26938v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is increasingly served across geo-distributed cloud and edge infrastructures, where wide-area latency, cross-region egress cost, and…
- arXiv cs.AIresearchBeyond Policy Discrepancy: Capability-Aware Multi-Teacher On-Policy Distillation
arXiv:2610.26950v2 Announce Type: replace-cross Abstract: Multi-teacher on-policy distillation (MOPD) integrates domain specialists into a shared student, but determining how strongly each teacher should supervise remain…
- arXiv cs.AIresearchFoundPDE: A generative foundation model for data-driven symbolic discovery of partial differential equations
arXiv:2610.26963v1 Announce Type: cross Abstract: Discovering governing partial differential equations (PDEs) from observed data is a central inverse problem in computational science and engineering: the goal is not only…
- arXiv cs.AIresearchSZED at ArGuard Shared Tasks: Multi-Task Label-Attention and Cross-Modal Fusion for Arabic Hateful Meme Detection
arXiv:2610.26972v1 Announce Type: cross Abstract: We present SZED's submission to ArGuard 2026 Track A: Arabic hateful meme detection. The task has two parts: binary classification (A1) and fine-grained multi-label taggi…
- arXiv cs.AIresearchDynamic Dual-Feedback Conformal Inference for Time Series Forecasting
arXiv:2610.26987v1 Announce Type: cross Abstract: Quantifying uncertainty in time series forecasting is particularly demanding because sequential data exhibit temporal dependence and are prone to distributional changes.…
- arXiv cs.AIresearch3D-MoE: Complementarity-Guided Hardware-Software Co-Design for MoE Decode on 3D-Stacked NMP
arXiv:2610.26991v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) have become a mainstream way to scale Large Language Models (LLMs), because each token activates only a small subset of experts, reducing inferen…
- arXiv cs.AIresearchCoASFL: Coupled Consistency Optimization for Asynchronous Split Federated Learning
arXiv:2610.26992v1 Announce Type: cross Abstract: Split Federated Learning (SFL) has emerged as a promising paradigm for training large-scale deep models on resource-constrained edge devices. Although asynchronous SFL al…
- arXiv cs.AIresearchHierDTA: Hierarchical Structure-Aware Representation Learning for Drug--Target Affinity Prediction
arXiv:2610.27001v1 Announce Type: cross Abstract: Drug--target affinity (DTA) prediction plays an important role in computer-aided drug discovery, where reliable computational models can help prioritize compound--protein…
- arXiv cs.AIresearchExploration via Activation-Space Steering for Reinforcement Learning with Verifiable Rewards
arXiv:2610.27012v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) trains a language model by sampling responses, scoring them with an automatic verifier, and updating the policy from…
- arXiv cs.AIresearchReliable Estimation of Differential Privacy under Selection Bias
arXiv:2610.27021v1 Announce Type: cross Abstract: Statistical privacy audits are essential for verifying the theoretical privacy guarantees of differentially private (DP) mechanisms. Auditors typically use Membership Inf…