Search: “reasoning”

TacO: Benchmarking Tactile Sensors for Object Manipulation

arXiv:2605.21976v1 Announce Type: new Abstract: Vision-based learning from demonstrations has achieved remarkable success in enabling robots to perform manipulation tasks and high-level semantic reaso

safetyarxiv-cs-ro

Token-Level LLM Collaboration via FusionRoute

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DGX agent

arXiv:2601.05106v4 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strengths across diverse domains. However, achieving strong performance across these domains with a singl

model-releasesarxiv-cs-cl

22 May 2026

Towards Clinically Interpretable Ophthalmic VQA via Spatially-Grounded Lesion Evidence

arXiv:2605.22414v1 Announce Type: new Abstract: Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmology, where retinal fundus photography is essential f

Transcription and Recognition of Italian Parliamentary Speeches Using Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2603.28103v2 Announce Type: replace-cross Abstract: Parliamentary proceedings represent a rich yet challenging resource for computational analysis, particularly when preserved only as scanned hi

Translating Signals to Languages for sEMG-Based Activity Recognition

arXiv:2605.22403v1 Announce Type: new Abstract: Surface electromyography (sEMG) signal-based activity recognition has attracted increasing research attention in recent years. To develop accurate sEMG

researcharxiv-cs-cv

Local Ai

VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals

arXiv:2605.20742v1 Announce Type: new Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly

local-aiarxiv-cs-ai

Visual-Advantage On-Policy Distillation for Vision-Language Models

arXiv:2605.21924v1 Announce Type: new Abstract: On-policy knowledge distillation has proven effective for language models, yet its application to vision-language models (VLMs) remains underexplored. W

What Does the Caption Really Say? Counterfactual Phrase Intervention for Compositional Data Selection in Vision-Language Pretraining

arXiv:2605.22651v1 Announce Type: new Abstract: CLIP-style contrastive pretraining typically curates web-scale image-text pairs using sample-level filtering signals, often based on pair-level alignmen

safetyarxiv-cs-cv

'Would You Want an AI Tutor?' Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom

arXiv:2503.02885v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following ea

safetyarxiv-cs-cl

Agents

A Semantic and Occlusion-Aware GM-PHD Filter

arXiv:2605.20666v1 Announce Type: new Abstract: This paper proposes a new birth model including semantic information derived from deep learning to create an occlusion-aware Gaussian Mixture Probabilit

agentsarxiv-cs-ro

Bayesian Preference Learning for Test-Time Steerable Reward Models

arXiv:2602.08819v2 Announce Type: replace-cross Abstract: Reward models are central to aligning language models with human preferences via reinforcement learning (RL). As RL is increasingly applied to

safetyarxiv-cs-cl

Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs

arXiv:2605.21027v1 Announce Type: new Abstract: Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional

safetyarxiv-cs-cl

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning

arXiv:2605.21177v1 Announce Type: cross Abstract: This work presents extsc{ChunkFT}, a memory-efficient fine-tuning framework that reformulates full-parameter fine-tuning around a dynamically activate

Agents

Code Generation by Differential Test Time Scaling

arXiv:2605.20473v1 Announce Type: cross Abstract: Test-time scaling has emerged as a promising approach for improving code generation by exploring large solution spaces at inference time. However, exi

agentsarxiv-cs-lg

Complementing reinforcement learning with SFT through logit averaging in the post training of LLMs

arXiv:2605.20555v1 Announce Type: new Abstract: We introduce a novel method that averages the logits of a frozen reference policy (e.g., SFT) and a trainable policy, and incorporate the method into Gr

safetyarxiv-cs-lg

CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning

arXiv:2605.20247v1 Announce Type: cross Abstract: Catastrophic forgetting remains a major obstacle to continual learning in large language models (LLMs) and vision--language models (VLMs). Although Mi

DC-LA: Difference-of-Convex Langevin Algorithm

arXiv:2601.22932v2 Announce Type: replace Abstract: We study a sampling problem whose target distribution is pi propto exp(-f-r) where the data fidelity term f is Lipschitz smooth while the regularize

applicationsarxiv-cs-lg

DEL: Digit Entropy Loss for Numerical Learning of Large Language Models

arXiv:2605.20369v1 Announce Type: new Abstract: Number prediction stands as a fundamental capability of large language models (LLMs) in mathematical problem-solving and code generation. The widely ado

Deltaynamics: Language-Based Representation for Inferring Rigid-Body Dynamics From Videos

arXiv:2605.20576v1 Announce Type: new Abstract: Inferring rigid-body physical states and properties from monocular videos is a fundamental step toward physics-based perception and simulation. Existing

Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs

arXiv:2605.20382v1 Announce Type: new Abstract: Language models are trained to follow instructions, but they are also powerful pattern completers. What happens when these two objectives conflict? We c

Do Vision--Language Models Understand 3D Scenes or Just Catalogue Objects?

arXiv:2605.20448v1 Announce Type: new Abstract: Vision--language models reliably name objects in a scene, but do they represent the 3D layout those objects inhabit? We introduce a 3,034-sample human-c

Efficient Table QA via TableGrid Navigation and Progressive Inference Prompting

arXiv:2605.20254v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown promising results on NLP tasks, however, their performance on tabular data still needs research attention, bec

researcharxiv-cs-cv

END: Early Noise Dropping for Efficient and Effective Context Denoising

arXiv:2502.18915v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of natural language processing tasks. However, they are of

FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition

arXiv:2605.20892v1 Announce Type: new Abstract: Fine-grained fruit classification is a critical yet challenging task in agricultural computer vision, primarily hindered by a severe shortage of high-qu

applicationsarxiv-cs-cv

FusionCell: Cross-Attentive Fusion of Layout Geometry and Netlist Topology for Standard-Cell Performance Prediction

arXiv:2605.20287v1 Announce Type: cross Abstract: Standard cells form the building blocks of digital circuits, so their delay and power critically influence chip-level performance; yet characterizatio

researcharxiv-cs-cv

GradeLegal: Automated Grading for German Legal Cases

arXiv:2605.21076v1 Announce Type: new Abstract: Grading German legal exam solutions faces growing volumes and a shortage of qualified graders, delaying feedback and creating a bottleneck. At the same

applicationsarxiv-cs-cl

Holistic Reliability Propagation: Decoupling Annotation and Prediction for Robust Noisy-Label

arXiv:2605.20725v1 Announce Type: new Abstract: Learning with noisy labels in multimedia classification often combines external annotations and model predictions into a single reliability weight, even

applicationsarxiv-cs-cv

Tutorials

Jointly Learning Predicates and Actions Enables Zero-Shot Skill Composition

arXiv:2605.20648v1 Announce Type: new Abstract: Learning from Demonstration (LfD) enables robots to learn complex behaviors from expert examples, yet existing approaches often fail to generalize to ne

tutorialsarxiv-cs-ro

LEAP: A closed-loop framework for perovskite precursor additive discovery

model-releasesarxiv-cs-lg

arXiv:2605.20242v1 Announce Type: new Abstract: Efficient discovery of precursor additives is essential for improving the performance of perovskite solar cells, yet the large chemical space makes conv

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

arXiv:2602.06025v2 Announce Type: replace Abstract: Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offl

Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases

arXiv:2605.20314v1 Announce Type: new Abstract: This work investigates the ``small-vs-large gap'', where repeating on fewer samples can lead to compute saving during training compared to using a large

researcharxiv-cs-lg

Leveraging Vision-Language Models to Detect Attention in Educational Videos

arXiv:2605.20211v1 Announce Type: new Abstract: Educational videos are a cornerstone of remote and blended learning. However, learners' fluctuating attention remains a significant barrier to effective

NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding

arXiv:2605.20525v1 Announce Type: cross Abstract: We present NeuroQA, a large-scale benchmark for visual question answering in 3D brain magnetic resonance imaging (MRI), with 56,953 QA pairs from 12,9

Local Ai

OSGNet with MLLM Reranking @ Ego4D Episodic Memory Challenge 2026

arXiv:2605.20818v1 Announce Type: new Abstract: In this report, we present our champion solutions for the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge at CVPR 20

local-aiarxiv-cs-cv

PointACT: Vision-Language-Action Models with Multi-Scale Point-Action Interaction

arXiv:2605.21414v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation by leveraging large pretrained vision-languag

safetyarxiv-cs-cv

Tutorials

Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues

arXiv:2605.20195v1 Announce Type: new Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core

tutorialsarxiv-cs-cl

QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs

arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res

Refining and Reusing Annotation Guidelines for LLM Annotation

arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention

Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis

arXiv:2605.20277v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have rapidly advanced as general-purpose multimodal assistants, yet their deployment in 3D Computed Tomography (CT

safetyarxiv-cs-cv

Agents

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved

agentsarxiv-cs-cl

Tutorials

Task-Routed Mixture-of-Experts with Cognitive Appraisal for Implicit Sentiment Analysis

arXiv:2605.20916v1 Announce Type: new Abstract: Implicit sentiment analysis is challenging because sentiment toward an aspect is often inferred from events rather than expressed through explicit opini

tutorialsarxiv-cs-cl

TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos

arXiv:2605.21443v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing eval

Temporal Counterfactual Explanations of Behaviour Tree Decisions

arXiv:2509.07674v2 Announce Type: replace Abstract: Explainability, in particular, the ability for robots to explain why they have made a decision or behaved in a certain way, is a critical tool in he

researcharxiv-cs-ro

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media

arXiv:2605.21338v1 Announce Type: new Abstract: LLMs have demonstrated exceptional proficiency in a wide range of NLP tasks. However, a notable gap remains in practical data analysis scenarios, partic

TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization

arXiv:2605.21318v1 Announce Type: new Abstract: Large language models (LLMs) are highly sensitive to the prompts used to specify task objectives and behavioral constraints. Many recent prompt optimiza

The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure?

arXiv:2605.20749v1 Announce Type: new Abstract: Gated Linear Units (GLU) and their variants are widely adopted in modern open-source large language model architectures and consistently outperform thei

researcharxiv-cs-lg

The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering

arXiv:2605.20745v1 Announce Type: cross Abstract: Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they

The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents

arXiv:2605.20544v1 Announce Type: cross Abstract: Vision-language models (VLMs) are used as high-level planners for embodied agents, translating natural language instructions and visual observations i