Search: “framework”

QuoVLA: Quotient Space for Vision-Language-Action Models

arXiv:2605.24890v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models commonly adapt pretrained Vision-Language Models (VLMs) to robot control by mapping visual observations and lang

researcharxiv-cs-cv

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RACT: Retrieval Augmented Column-Table Learning and Prediction for Multi-Table Schema Matching

DGX agent

arXiv:2606.07843v1 Announce Type: cross Abstract: Schema matching, a critical task for integrating data from diverse sources, seeks to identify correspondences between columns across different schemas

researcharxiv-cs-lg

9 Jun 2026

RadOT-Eval: Auditable Structured-Evidence Transport for Radiology Report Evaluation

arXiv:2606.08769v1 Announce Type: cross Abstract: Automatic evaluation is critical for high-stakes text generation, where errors often involve omitted findings, hallucinated content, polarity reversal

Real-IKEA: Physical Fidelity is the Prerequisite for Robust Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.08564v1 Announce Type: new Abstract: Robotic manipulation robustness often founders on the physics gap between simplified simulations and the resistance-laden real world. In this work, we e

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

arXiv:2606.09380v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a leading paradigm for improving the reasoning ability of large language models throu

Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator

arXiv:2606.08652v1 Announce Type: cross Abstract: Routine full-disk EUV imaging has been available only since the modern era, such as SOHO and SDO. To extend EUV coronal context into earlier periods,

ReCoVLA: VLM-Guided Reward Compilation for Failure Recovery in Vision-Language-Action Policies

arXiv:2606.09630v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies provide strong priors for language-conditioned manipulation, but remain brittle in off-nominal states requiring

REFINE: Super-efficient 3D Gaussian Splatting Pruning via Rendering-Free Primitive Importance

model-releasesarxiv-cs-cv

arXiv:2606.09074v1 Announce Type: new Abstract: Existing pruning methods for 3D Gaussian splatting (3DGS) suffer from either severe quality degradation or prohibitive computational overhead. In this p

Agents

Reflection in the Dark: Exposing and Escaping the Black Box in Reflective Prompt Optimization

arXiv:2603.18388v2 Announce Type: replace Abstract: Automatic prompt optimization (APO) has emerged as a powerful paradigm for improving LLM performance without manual prompt engineering. Reflective A

agentsarxiv-cs-ai

ReGIL: Retrieval-Guided Imitation Learning from a Single Demonstration

arXiv:2606.09381v1 Announce Type: new Abstract: Learning robot manipulation policies with deep neural networks from a single demonstration remains highly challenging, as even small deviations from the

safetyarxiv-cs-ro

Region-Wise Correspondence Prediction between Manga Line Art Images

arXiv:2509.09501v4 Announce Type: replace Abstract: Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks

Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations

arXiv:2606.08104v1 Announce Type: new Abstract: Soft-bodied organisms such as octopuses and elephant trunks exhibit remarkable morphological adaptability, dynamically reconfiguring body shape and stif

safetyarxiv-cs-ro

Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning

arXiv:2606.08436v1 Announce Type: new Abstract: The task of temporal answer grounding in instructional video (TAGV), which aims to locate precise video segments that respond to natural language querie

Repair Before Veto, When Repair Is Hidden: Quantum-Accessible Features for Repair-Augmented Constraint Learning

arXiv:2606.08020v1 Announce Type: cross Abstract: Hard-constraint decision systems usually veto infeasible candidates. This is too rigid when the system can act: if a known affordable repair would mak

Agents

RepoLaunch: Automating Build and Management of Code Repositories across Languages and Platforms

arXiv:2603.05026v2 Announce Type: replace-cross Abstract: Language model (LM) agents have driven substantial progress in automated software engineering (SWE), yet building and testing software reposit

agentsarxiv-cs-lg

RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction

arXiv:2603.12666v2 Announce Type: replace-cross Abstract: Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule. Although molecular large language models (L

Rewrite to Translate, Translate to Reward: Reinforcement Learning for Source Rewriting in Machine Translation

arXiv:2606.08011v1 Announce Type: cross Abstract: Although directly prompting off-the-shelf Large Language Models (LLMs) to generate meaning-preserving source rewrites can effectively enhance Machine

Tutorials

RGB-S: Image-Aligned Tactile Saliency for Robust Dexterous Manipulation

arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. Ho

tutorialsarxiv-cs-cv

RiskNet: A large-scale dataset of AI risk incidents from news with alignment and multi-dimensional annotations

arXiv:2606.08376v1 Announce Type: cross Abstract: As artificial intelligence (AI) systems are increasingly deployed across socially consequential domains, reports of AI-related harms and failures have

Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks

arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20

researcharxiv-cs-lg

Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?

arXiv:2606.08063v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in visual understanding, yet their performance degrades significantly un

Applications

RT-SDGOD: Real-Time Single-Domain Generalized Object Detection

arXiv:2606.09367v1 Announce Type: new Abstract: In real-world deployment under strict real-time constraints, weather and imaging variations induce significant distribution shifts, severely degrading d

applicationsarxiv-cs-cv

SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning

arXiv:2511.05355v3 Announce Type: replace Abstract: Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action

safetyarxiv-cs-lg

SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization

arXiv:2606.08496v1 Announce Type: cross Abstract: Although Sparse Autoencoders (SAEs) have mitigated the opacity of large language models (LLMs) by decomposing dense representations into sparse featur

researcharxiv-cs-lg

Safe, Fluent and Acceptable Motion Generation and Execution for Human--Robot Interaction in Manufacturing Environments

arXiv:2606.08741v1 Announce Type: new Abstract: Robots operating in human environments must not only ensure physical safety but also exhibit behaviors that are understandable, fluent, and acceptable t

safetyarxiv-cs-ro

Safe-RULE: Safe Reinforcement UnLEarning

arXiv:2606.09559v1 Announce Type: cross Abstract: Offline safe reinforcement learning (Safe RL) enables policy learning without online interactions, making it suitable for safety-critical systems such

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

arXiv:2606.08037v1 Announce Type: cross Abstract: Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy fo

SafeRun: Enabling Determinism in LLM Planning for Running

arXiv:2606.09027v1 Announce Type: cross Abstract: Large Language Models enable flexible natural-language planning but remain unreliable in determinism-critical domains due to their probabilistic natur

SAGE: Shape-Adapting Gated Experts for Adaptive Histopathology Image Segmentation

arXiv:2511.18493v4 Announce Type: replace-cross Abstract: The significant variability in cell size and shape continues to pose a major obstacle in computer-assisted cancer detection on gigapixel Whole

SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models

arXiv:2606.07705v1 Announce Type: cross Abstract: Although multi-objective reinforcement learning (MORL) is central to aligning large language models with complex human preferences, the prevailing pra

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism

arXiv:2606.09377v1 Announce Type: cross Abstract: Formal neural network verification -- proving that a network satisfies safety properties for all inputs in a specified domain -- is bounded in practic

Scaling Participation in Modular AI Systems

arXiv:2606.07812v1 Announce Type: new Abstract: Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by t

SceneConductor: 3D Scene Generation from Single Image with Multi-Agent Orchestration

arXiv:2606.08402v1 Announce Type: cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context fro

SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

model-releasesarxiv-cs-cv

arXiv:2602.09809v2 Announce Type: replace Abstract: Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorr

See More, Match Better: Multi-Source Feature Fusion for Two-View Correspondence Learning

arXiv:2606.09262v1 Announce Type: new Abstract: Two-view correspondence learning aims to distinguish true correspondences (inliers) from false ones (outliers) in image pairs by leveraging their underl

See More, Think Deeper: Query-Expanded Visual Evidence and Answer-Clue Guided Reflection for Long Video Understanding

arXiv:2606.09064v1 Announce Type: cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have enabled performance on long-video understanding tasks. However, existing methods stil

Seeing is Believing: Aligning Prompt Rewriting with Visual Anchors for Text-to-Image Generation

arXiv:2606.08492v1 Announce Type: cross Abstract: Despite the impressive capabilities of text-to-image (T2I) models, an intent-generation gap often persists due to the brevity and ambiguity of user pr

Segment-level Tree Search for Long Meeting Document Summarization

arXiv:2606.08445v1 Announce Type: cross Abstract: Meeting documents are challenging to summarize due to their length and complex conversational structure. Existing approaches typically adopt multi-sta

Segmentation-Assisted Brain MRI Synthesis with Cross-Image Multi-Contrast Feature Memory Bank Retrieval Augmentation

arXiv:2606.08421v1 Announce Type: new Abstract: Multi-contrast brain MRI provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scannin

researcharxiv-cs-cv

Self-Evolving Scientific Agent Discovers Generalizable Physically-Reasoned Fluid Control

arXiv:2606.08405v1 Announce Type: new Abstract: While data-intensive deep reinforcement learning can optimize complex control policies, scientific discovery in physical systems fundamentally requires

Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directions

arXiv:2606.09568v1 Announce Type: new Abstract: The growing complexity of self-adaptive and self-organising systems, fuelled by advances in Artificial Intelligence (AI), has made them increasingly dif

Agents

Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation

arXiv:2606.09236v1 Announce Type: cross Abstract: Autonomous Racing has seen remarkable progress through deep Reinforcement Learning (RL), primarily for four-wheeled vehicles. However, motorbikes intr

agentsarxiv-cs-ai

Self-supervised Learning Matters: A Simple Ensemble Solution for Micro-Gesture Recognition

arXiv:2606.09261v1 Announce Type: new Abstract: In this paper, we present XInsight Lab's solution to the micro-gesture classification track of the 4th MiGA Challenge at IJCAI 2026, in which our soluti

researcharxiv-cs-cv

Semantic Cache Distillation: Efficient State Transfer via Reuse and Selective Patching

arXiv:2606.07684v1 Announce Type: cross Abstract: Disaggregated serving alleviates memory bottlenecks in Large Language Model (LLM) inference but creates a severe communication bottleneck: transmittin

SemDINO: A DINOv3-Driven Network for Cross-Temporal Semantic Alignment in Change Detection

arXiv:2606.09772v1 Announce Type: new Abstract: Semantic change detection (SCD) aims to simultaneously locate land-cover changes and identify semantic categories before and after transition. However,

Semi-supervised Source Detection in Astronomical Images: New Benchmark and Strong Baseline

model-releasesarxiv-cs-cv

arXiv:2606.09219v1 Announce Type: new Abstract: Source detection in modern observational astronomy is a cornerstone for localizing and identifying stellar sources accurately. It is crucial for studies

SENTRY: Statistical Reliability Analysis of Vision Transformers Under Soft Errors

arXiv:2606.07620v1 Announce Type: cross Abstract: With the growth of Vision Transformers in safety-critical domains like autonomous systems and medical imaging, ensuring their reliability against soft

Set-Based Transformer for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging

arXiv:2606.08324v1 Announce Type: cross Abstract: Passive long-wave infrared (LWIR) hyperspectral imaging under a standoff geometry depends on atmospheric absorption and emission, as well as reflected