Search: “models”

Distilling LLM Reasoning into Graph of Concept Predictors

arXiv:2602.03006v3 Announce Type: replace Abstract: Deploying Large Language Models (LLMs) for discriminative workloads is often limited by inference latency, compute, and API costs at scale. Active d

Emergent Object Binding Has a Finite Spatial Horizon

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DGX agent

arXiv:2610.00006v1 Announce Type: new Abstract: Pretrained Vision Transformers encode whether two image patches belong to the same object. This IsSameObject signal is decodable from frozen patch embed

researcharxiv-cs-cv

2 Oct 2026

eRLT: Efficient VLA Reinforcement Learning via Action-Relevant Token Routing

arXiv:2610.00913v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide strong behavioral priors for robotic manipulation, yet efficiently adapting them to downstream tasks remains

researcharxiv-cs-ro

Exposing the Cost of Deep Learning Audio Development

arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and car

applicationsarxiv-cs-ai

FedMAD: Modulation-Aware Directional Aggregation for Federated Learning in Remote Sensing Image Classification

arXiv:2610.00693v1 Announce Type: new Abstract: Federated learning (FL) has recently attracted increasing attention in remote sensing (RS) since it enables collaborative model training across decentra

safetyarxiv-cs-cv

FORTE: Adaptive Scoring and Exact Keyframe Selection for Long-Video Question Answering

arXiv:2610.00573v1 Announce Type: new Abstract: Query-aware keyframe selection enables multimodal large language models (MLLMs) to process long videos using only a small set of question-relevant frame

Fusing Visual and Textual Representations via Multi-layer Fusing Transformers for Vietnamese Visual Question Answering

arXiv:2610.01637v1 Announce Type: new Abstract: In recent decades, artificial intelligence has made significant progress in understanding and interacting with images. One of the important applications

applicationsarxiv-cs-cv

GLoC-EHR: Evidence-Cited Clinical Reasoning over Global Context and Local EHR Events

arXiv:2610.01076v1 Announce Type: new Abstract: Structured electronic health records (EHRs) contain a patient's clinical trajectory as a sequence of clinical codes. Answering clinical questions from s

local-aiarxiv-cs-lg

Gradient-Aligned Pair Selection for Personalized Preference Optimization

arXiv:2610.00061v1 Announce Type: new Abstract: Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Dir

Greed Is Learned: Visible Incentives as Reward-Hacking Triggers

arXiv:2606.16914v2 Announce Type: replace Abstract: Safety evaluations test a policy on prompts that omit the incentive information deployment supplies: a commission, a performance score, a dashboard

In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners

arXiv:2610.01712v1 Announce Type: new Abstract: In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters. While much of the existing the

In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement

arXiv:2601.22169v2 Announce Type: replace-cross Abstract: Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e

Integrating Fairness and Explainability in a Multiple Instance Reinforcement Learning System

arXiv:2610.00035v1 Announce Type: new Abstract: Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningf

safetyarxiv-cs-lg

Agents

InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation

arXiv:2610.02196v1 Announce Type: cross Abstract: We study test-time evolution for humanoid loco-manipulation: solving tasks that a controller was never trained for by repurposing its existing skills,

agentsarxiv-cs-cv

InterviewSim: A Scalable Framework for Interview-Grounded Personality Simulation

arXiv:2602.20294v2 Announce Type: replace-cross Abstract: Simulating real personalities with large language models requires grounding generation in authentic personal data. Existing evaluation approac

iSEE: Object Permanence Through Self-Supervision

arXiv:2610.01201v1 Announce Type: new Abstract: Object permanence, keeping track of an object's identity and position while it is occluded, is central to video representations that track, predict and

local-aiarxiv-cs-cv

Judgement in the Age of Jev: From Evaluation Scarcity to Evaluation Abundance

arXiv:2610.01231v1 Announce Type: cross Abstract: Generative artificial intelligence has reduced the cost of producing plausible symbolic artefacts, leading recent organisation scholarship to identify

applicationsarxiv-cs-ai

Learning a Resolution-Consistent Jacobian Field for Bio-Inspired Rigid-Soft Finger

arXiv:2610.01668v1 Announce Type: new Abstract: Bio-inspired tendon-driven rigid-soft coupled dexterous fingers exhibit strong nonlinearity and configuration-dependent sensitivity, making accurate mod

local-aiarxiv-cs-ro

Learning Goal-Reaching Quasimetric Geometry From Finite-Time Reachability

arXiv:2610.00778v1 Announce Type: new Abstract: In goal-conditioned reinforcement learning (GCRL), quasimetric learning models goal-reaching costs as quasimetric distances, connecting local constraint

Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon

arXiv:2610.00422v1 Announce Type: cross Abstract: Neural combinatorial optimization typically assumes a centralized solver that reads the whole instance. We study the opposite: combinatorial optimizat

local-aiarxiv-cs-ai

LensBridge: Frequency-Guided Compound Degradation Adaptation for Lens Aberration Correction and Veiling Glare Removal

arXiv:2610.00318v1 Announce Type: cross Abstract: Simplified optical systems often exhibit residual lens aberrations and Veiling Glare (VG), resulting in spatially varying blur and contrast reduction.

Machine Translation for Sign Languages

arXiv:2610.00881v1 Announce Type: new Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation s

applicationsarxiv-cs-cv

Make Sparse Rewards Count: Density-Aware Reward Aggregation for Multi-Reward RL

arXiv:2610.00574v1 Announce Type: new Abstract: Multi-reward reinforcement learning trains large language models to satisfy multiple behavioral objectives simultaneously. Reward-wise normalization, as

safetyarxiv-cs-lg

Mean field games as a tool for AI safety: a worked example from the July 2026 Hugging Face incident

arXiv:2610.00902v1 Announce Type: cross Abstract: One way to make AI systems safe is to shape what the system is: its objective and dispositions. We take a complementary route: treat the agents' chara

Agents

Memetic Trojans: Social Contagions as Carriers of Adversarial Payloads in Agent Networks

arXiv:2610.00430v1 Announce Type: cross Abstract: Autonomous large language model (LLM) agents increasingly interact in network environments where adversarial content can propagate between agents. Kno

agentsarxiv-cs-ai

Agents

MemFit: Efficient Long-Term Agentic Memory

arXiv:2610.00872v1 Announce Type: new Abstract: Long-term memory systems for large language models (LLMs) have gained popularity for extending reasoning capabilities across applications. Current memor

agentsarxiv-cs-ai

Misalignment of Low-Loss Regions Causes Grokking

arXiv:2610.00620v1 Announce Type: cross Abstract: Grokking refers to the delayed emergence of validation-set generalization after a model has already overfit the training set. Although first observed

MoLE: Mixture of Latent Experts for Complementary Visual Reasoning

arXiv:2610.01917v1 Announce Type: cross Abstract: Latent visual reasoning equips vision--language models with continuous intermediate states that can process visual evidence without explicit textual r

MOVE: Multimodal Open-world Verification and Expansion for Graph Learning

arXiv:2610.00268v1 Announce Type: new Abstract: Multimodal graph learning faces a fundamental challenge: new classes may emerge after deployment, while models are trained with a fixed label space. Exi

Multi-agent Auditory Scene Analysis: Improved Localization Speed and Robustness by Multi-beamformed Speech Quality Feedback

arXiv:2610.00538v1 Announce Type: cross Abstract: A real-time auditory scene analyzer (ASA) aims to carry out the tasks of locating, separating and classifying the sound sources present in a given aco

local-aiarxiv-cs-ai

Multi-Task Anti-Causal Learning for Reconstructing Urban Events from Residents' Reports

arXiv:2603.11546v2 Announce Type: replace Abstract: Many real-world machine learning tasks are anti-causal: they require inferring latent causes from observed effects. In practice, we often face multi

applicationsarxiv-cs-lg

MVDG: Efficient Multi-view 3D Disambiguation on Unconstrained Real-World Images

arXiv:2610.01098v1 Announce Type: new Abstract: Illusory matches between distinct yet visually similar 3D surfaces--doppelgangers--remain a fundamental obstacle for large-scale, in-the-wild 3D reconst

local-aiarxiv-cs-cv

ODDR: One-Step Deshadow Diffusion via Reward Guidance

arXiv:2610.01291v1 Announce Type: new Abstract: Recent advances in deep learning for shadow removal have significantly enhanced image quality and realism. However, most approaches rely on real-world p

applicationsarxiv-cs-cv

Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AI

arXiv:2610.00682v1 Announce Type: new Abstract: Large language models (LLMs) increasingly underpin scientific AI applications that reason over structured knowledge, from biomedical question answering

Port-Hamiltonian Neural Networks for Systems with Multiple Asymptotically Stable Equilibria

arXiv:2610.01356v1 Announce Type: new Abstract: Stable port-Hamiltonian neural networks certify asymptotic stability by construction. Yet, their Hamiltonian is a global Lyapunov function with a single

Reformulation-Contrastive Learning for Mixed Integer Programs

arXiv:2610.00730v1 Announce Type: new Abstract: Mixed-integer linear programs (MILP) model many real-world decision problems, motivating machine-learning methods that exploit recurring structure to ac

applicationsarxiv-cs-lg

RelationVGGT: Visual Geometry Transformers for 3D Spatial Relation Segmentation

arXiv:2610.00970v1 Announce Type: cross Abstract: Recent advances in 3D reconstruction have progressed from per-scene optimization to feed-forward inference, and semantic scene understanding has follo

Representation Transitions Reveal Emerging Safety Risks in Multi-Turn LLM Agents

arXiv:2610.00400v1 Announce Type: cross Abstract: Multi-turn attacks on agentic systems can compose individually permissible actions into harmful outcomes, challenging defenses that assess actions or

Reverse Item Response Theory for Sparsity-Robust Ranking in Fragmented Cancer Drug-Response Matrices

arXiv:2610.00002v1 Announce Type: new Abstract: We introduce reverse Item Response Theory (IRT) to pharmacogenomic drug-response analysis by treating cancer types as latent 'subjects' with resistance

Robust Is Salient: An Informed Adversary Moves the Optimal Signal onto the Salience Pole

arXiv:2610.00233v1 Announce Type: new Abstract: When an informed adversary shares the audience of a constrained signalling channel, the signal that best protects the truth is the signal that best desc

Roto-translated Local Coordinate Frames For Interacting Dynamical Systems

arXiv:2110.14961v4 Announce Type: replace Abstract: Modelling interactions is critical in learning complex dynamical systems, namely systems of interacting objects with highly non-linear and time-depe

Tutorials

Seeing the City or Recognizing the Place? What Street-View Imagery Adds Beyond Existing Urban Data in VLM Urban Sensing

arXiv:2610.00031v1 Announce Type: new Abstract: Street-view imagery is increasingly used to infer urban attributes, but predictive accuracy alone does not reveal how much a photograph contributes beyo

tutorialsarxiv-cs-cv

Signal-Noise Factorization Isolates Nuisance Variation into Removable Subspaces

arXiv:2610.00751v1 Announce Type: cross Abstract: Recent theoretical work identified fundamental properties of representation geometry that shape inference ability of deep neural networks. These inclu

Signed Lexical Confidence for Risk-Calibrated Intent Routing

arXiv:2610.00262v1 Announce Type: cross Abstract: Selective intent routing allows an assistant to act on reliable predictions while deferring uncertain requests. Standard confidence scores primarily r

SpikeMoE: Brain-Inspired Competitive Routing for Flexible Spiking Mixture-of-Experts

arXiv:2610.01418v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) enable event-driven computation through biologically inspired dynamics at the neuronal scale, while Mixture-of-Experts (M

Subtoken Vision Transformer for Fine-grained Recognition

arXiv:2607.09086v2 Announce Type: replace Abstract: We present Subtoken Vision Transformer (SubViT), a selective image tokenization method for fine-grained visual recognition. Standard Vision Transfor

local-aiarxiv-cs-cv

Surface-volume self-supervised representation learning of brain MRI for genetic discovery

arXiv:2610.02114v1 Announce Type: new Abstract: Existing genome-wide association studies (GWAS) of brain imaging provide predefined or deep-learning-derived imaging phenotypes, yet these phenotypes co

Symmetry Discovery in Quantum Learning: Observable-Level and Task-Level Inference from Finite Measurements

arXiv:2610.00157v1 Announce Type: cross Abstract: Symmetry reduces the capacity of a quantum learning model, but the imposed group must match both the measured information and the label transformation

safetyarxiv-cs-lg