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Align Before You Combine: Reference Space Calibration for Supervision Without Ground Truth

arXiv:2610.09525v1 Announce Type: new Abstract: We introduce a calibration-first framework that produces supervision scores without access to ground-truth labels or a shared annotation space. Our fram

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Human DGX agent

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Allocation Stability and Wald Inference under Variance-Aware UCB

DGX agent

arXiv:2412.08843v3 Announce Type: replace-cross Abstract: Allocation stability is often used to justify Gaussian inference from bandit data, but when is it necessary? In this paper, we address this qu

safetyarxiv-cs-lg

8 Oct 2026

An Accuracy--Information Tradeoff for Loss-Difference Conditional Mutual Information

arXiv:2610.09206v1 Announce Type: new Abstract: Loss-difference conditional mutual information (ld-CMI) uses the smallest of the standard observations in the supersample hierarchy of generalization bo

An AI-assisted conditioning and geological interpretation workflow for usage in implicit geological modeling

arXiv:2610.09871v1 Announce Type: cross Abstract: Implicit modeling and Relative Geologic Time are geological modeling techniques that enable more efficient, faster, less biased and more reproducible

An Empirical Study of Agent Skills' Downstream Utility

arXiv:2610.08875v1 Announce Type: cross Abstract: Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies

agentsarxiv-cs-lg

An extended deep energy method for thermo-mechanical crack propagation

arXiv:2610.09433v1 Announce Type: new Abstract: Thermo-mechanical fracture couples transient heat conduction on a cracked domain with a crack that grows as the temperature and the displacement evolve.

An Informational Curse of Horizon in Goal-Conditioned Policy Learning

arXiv:2610.09247v1 Announce Type: new Abstract: The difficulty of learning goal-reaching policies is often attributed to a 'curse of horizon' that manifests as bias accumulation in temporal-difference

An Invariant Tangent-Angle Descriptor and a Band U-Net for 2D Fragment Adjacency Prediction

arXiv:2610.09459v1 Announce Type: new Abstract: This paper addresses the prediction of adjacency between pairs of 2D fragments based on their contours. We improved the two-stage architecture proposed

An RRAM-based Hardware Implementation of a Radial Basis Function Neuron for Edge Classifiers

arXiv:2606.14739v2 Announce Type: replace-cross Abstract: The deployment of modern machine learning (ML) solutions on resource-constrained edge devices highlights implementation challenges. This is es

Local Ai

Anaximander: Interactively Running Geospatial Deep Learning Models on Any Compute Backend

arXiv:2610.09085v1 Announce Type: new Abstract: Applying deep learning models to satellite imagery from within geographic information systems (GIS) remains high-friction for remote sensing practitione

local-aiarxiv-cs-cv

Anytime-Feasible First-Order Optimization via Safe Sequential QCQP

arXiv:2511.19675v2 Announce Type: replace-cross Abstract: This paper presents the Safe Sequential Quadratically Constrained Quadratic Programming (SS-QCQP) algorithm, a first-order method for smooth i

agentsarxiv-cs-ro

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation

arXiv:2505.19912v3 Announce Type: replace Abstract: We present Adjacent Possible Exploration (APE), a selective fine-tuning method for adapting large language models that systematically explores param

ARCS: Towards Precise Text-to-SQL via Structured Disambiguation

arXiv:2610.09396v1 Announce Type: new Abstract: As text-to-SQL systems move beyond demonstrations toward real-world deployment, ambiguity in user questions becomes a primary source of errors. Such amb

Arctic Questions, Missing Answers: A Dataset and Benchmark for LLM Abstention in Arctic Science

arXiv:2610.09446v1 Announce Type: new Abstract: Large language models (LLMs) should abstain from scientific multiple-choice questions when no option is valid, but frequent abstention alone does not de

Are Parameter-Efficient Fine-tuning Methods Really Different?

arXiv:2610.09122v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) offers many parameterizations, yet their methodological and functional differences remain unclear. We compare six

Are We Really Benchmarking Forecasting Models? The Impact of Preprocessing on Time Series Performance

arXiv:2610.09096v1 Announce Type: new Abstract: While established literature underscores the pivotal role of preprocessing in forecasting accuracy, this stage remains largely overlooked in current res

Argos: Adapt Rich Geometric Priors for Generalizable Online Scene-Change-Detection

arXiv:2610.10181v1 Announce Type: new Abstract: Robots operating in dynamic environments require reliable detection of how their surroundings change over time. Existing learning-based methods largely

Hardware

Artificial intelligence pathways from weather to climate

arXiv:2610.09770v1 Announce Type: cross Abstract: Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models acros

hardwarearxiv-cs-lg

Ask the Expert: LLM-Guided Reinforcement Learning for Autonomous Cyber Defense

arXiv:2610.09337v1 Announce Type: cross Abstract: Policy-based reinforcement learning (RL) approaches have produced promising results for autonomous cyber defense; however, they are sample-inefficient

Attention-Mass Condensation for Sparse Decoding

arXiv:2602.06317v3 Announce Type: replace-cross Abstract: Attention-mass concentration creates an opportunity for sparse decoding, but retained mass alone does not guarantee a stable greedy decision:

researcharxiv-cs-cl

Attention via Black-Box Vector Search

arXiv:2610.10135v1 Announce Type: cross Abstract: Sparse attention mechanisms estimate attention over n tokens using a small subset of keys. Many existing approaches use maximum inner product search (

Auto-Regressive Models Need Structural Registers: Semantic Foresight Improves Coherent Driving Video Continuation

arXiv:2412.03758v4 Announce Type: replace Abstract: Front-view driving video continuation is a critical component for constructing sophisticated world models. However, maintaining long-term coherence

agentsarxiv-cs-cv

AutoAdapt: Automatic Domain Discovery Enables Low-Cost Extensibility

arXiv:2610.10349v1 Announce Type: new Abstract: Instruction-tuned models are deployed into environments where domains are heterogeneous and evolve, yet adding new domains or data typically requires co

Autonomous Driving Research Requires a Community-Driven Data Paradigm

arXiv:2610.08825v1 Announce Type: new Abstract: Autonomous driving has made remarkable progress, with recent AI advances enabling commercial deployments that are reshaping urban mobility. Yet the fiel

Average-Reward Reinforcement Learning for Multichain MDPs: A Hierarchical Decomposition Approach

arXiv:2610.10326v1 Announce Type: new Abstract: We study learning optimal policies in average-reward multichain Markov decision processes (MDPs), where the optimal gain may depend on the initial state

Backdooring Acoustic Foundation Models for Physically Realizable Triggers

arXiv:2610.09819v1 Announce Type: cross Abstract: Acoustic foundation models (AFMs) have democratized acoustic applications, enabling powerful models for tasks ranging from speech recognition to speak

BagDINO: Multi-View Baggage Re-Identification with DINOv3

arXiv:2610.10160v1 Announce Type: new Abstract: Mishandled checked baggage remains a recurrent issue in airport operations, and current recovery workflows still largely rely on tag-based tracking, whi

BanglaRhet: Benchmarking Classical and Transformer Models for Rhetorical and Persuasion Detection in Bangla Political Speech

arXiv:2610.09464v1 Announce Type: new Abstract: Political discourse often uses rhetorical and persuasive language to frame narratives, influence public opinion, and mobilize audiences. While Bangla na

Batch Augmentation with Unimodal Fine-tuning for Multimodal Fusion of Large Language Models

arXiv:2505.06592v2 Announce Type: replace Abstract: In this paper, we propose batch augmentation with unimodal fine-tuning for multimodal learning. We start with pre-trained unimodal models. We fine-t

researcharxiv-cs-cv

BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment

arXiv:2610.09026v1 Announce Type: cross Abstract: We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavior

BeatFlow-ECG: Rectified Flow for ECG Reconstruction from Indirect Wearable Signals

arXiv:2610.09052v1 Announce Type: new Abstract: Continuous cardiac monitoring outside clinical settings requires signals that are both informative and practical to collect during daily life. Electroca

Belief-Space Planning with Planner-Conditioned Estimator Error under Intermittent Observations

arXiv:2610.09207v1 Announce Type: new Abstract: Belief-space planners with separately designed or off-the-shelf estimators may have access to state-relevant information the estimator does not observe.

researcharxiv-cs-ro

Benchmarking Behavioral Steerability in Behavior Foundation Models

model-releasesarxiv-cs-ro

arXiv:2610.10198v1 Announce Type: new Abstract: Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve

Benign Overfitting under Heterogeneous Input Fusion

arXiv:2610.09340v1 Announce Type: new Abstract: Benign overfitting is extensively studied when learning from a single high-dimensional input, but its behavior under heterogeneous input fusion remains

Best Arm Identification for Bandits with Shifting Means

arXiv:2610.10488v1 Announce Type: cross Abstract: We study the best arm identification problem in a stochastic environment with a novel form of adversarial perturbations, which we coin Shifting Means.

Beyond Anonymous Captions: Grounding Character Identity in Video Captioning and Question Answering

arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-awa

Beyond Baseline Severity: Temporal and Disease-Specific Predictors of Depression Outcomes Following Mindfulness Interventions

arXiv:2610.08809v1 Announce Type: new Abstract: Depression severity among patients with chronic or acute medical conditions is influenced by a complex interaction of baseline psychological state, demo

Beyond Explanation: Debugging Medical Imaging Models via Concept Intervention

arXiv:2610.09031v1 Announce Type: new Abstract: Medical imaging models often operate as black boxes, limiting interpretability and systematic debugging. We introduce an easy-to-use, plug-and-play fram

researcharxiv-cs-cv

Beyond Group Splits: Specimen-Level Cross-Validation and Visual Attribution for Remaining-Shelf-Life Regression in Climacteric Fruit

arXiv:2610.09726v1 Announce Type: new Abstract: Estimating remaining shelf life (RSL) from images could provide affordable decision support for perishable produce, but evaluation protocols can substan

researcharxiv-cs-cv

Beyond Masks and Trajectories: Flow-Guided Latent Action Injection for Stable Surgical Video Generation

arXiv:2610.09800v1 Announce Type: new Abstract: Surgical video generation holds substantial potential for surgical education, simulation, and data augmentation, yet generating surgical videos with rea

safetyarxiv-cs-cv

Beyond Nominal Equilibria: Risk-Averse Multi-Population Mean-Field Games

arXiv:2610.09244v1 Announce Type: cross Abstract: Recent advances in mean-field games and its multi-population variants enable large-scale heterogeneous multi-agent systems to be modeled through repre

agentsarxiv-cs-lg

Beyond Outcome Rewards: Constructing and Assigning Retrieval Credit for Search Agents

arXiv:2610.10179v1 Announce Type: new Abstract: Search agents enable Large Language Models (LLMs) to iteratively retrieve and use information for complex multi-hop questions. Reinforcement Learning wi

agentsarxiv-cs-cl

Beyond Policy Support: Interaction Constrained Offline Reinforcement Learning for Autonomous Driving

arXiv:2610.09763v1 Announce Type: new Abstract: Offline reinforcement learning enables reward-driven policy improvement from fixed datasets without requiring online exploration, making it particularly

Beyond Reconstruction: What Matters in Action Tokenization for Robot Policies?

arXiv:2610.09170v1 Announce Type: new Abstract: Autoregressive action-token policies such as vision-language-action models require action tokenizers to translate discrete token sequences into precise

safetyarxiv-cs-ro

Applications

Beyond Reward Suppression: Near-Optimal Offline Attacks on Warm-Start Bandits with Bounded Rewards

arXiv:2610.10000v1 Announce Type: new Abstract: Adversarial attacks on bandits aim to mislead a learner toward a target arm while keeping the attack cost small. Existing attacks typically achieve this

applicationsarxiv-cs-lg

Beyond Risk Prediction: Evidence Grounding and Psychosocial Factor Verification for Explainable Suicide Risk Assessment

arXiv:2610.08842v1 Announce Type: new Abstract: Identifying suicide risk from social networking services (SNS) posts is important for detecting suicide-related signals in online environments. However,

researcharxiv-cs-cl

Beyond the Sycophancy Score: How Task, Model, and Pressure Shape LLM Yielding

arXiv:2610.08840v1 Announce Type: new Abstract: Large language models (LLMs) often abandon a correct answer, or endorse a user's position, once the user pushes back. This behavior, called sycophancy,

safetyarxiv-cs-cl

Bi-CamoDiffusion: A Boundary-informed Diffusion Approach for Camouflaged Object Detection

arXiv:2603.13357v2 Announce Type: replace Abstract: Bi-CamoDiffusion is introduced, an evolution of the CamoDiffusion framework for camouflaged object detection. It integrates edge priors into early-s