{"total":55,"rows":[{"id":"2503.01785","title":"Visual-RFT: Visual Reinforcement Fine-Tuning","created":"2025-03-03","cited_by_count":513,"area":"lr"},{"id":"2406.01584","title":"SpatialRGPT: Grounded Spatial Reasoning in Vision Language Models","created":"2024-06-03","cited_by_count":311,"area":"lr"},{"id":"2406.19389","title":"OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding","created":"2024-06-27","cited_by_count":127,"area":"lr"},{"id":"2505.12081","title":"VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning","created":"2025-05-17","cited_by_count":51,"area":"lr"},{"id":"2505.12448","title":"SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoning","created":"2025-05-18","cited_by_count":46,"area":"lr"},{"id":"2506.22624","title":"Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning","created":"2025-06-27","cited_by_count":44,"area":"lr"},{"id":"2411.17606","title":"HyperSeg: Towards Universal Visual Segmentation with Large Language Model","created":"2024-11-26","cited_by_count":33,"area":"lr"},{"id":"2506.21656","title":"Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs","created":"2025-06-26","cited_by_count":32,"area":"lr"},{"id":"2405.17427","title":"Reason3D: Searching and Reasoning 3D Segmentation via Large Language Model","created":"2024-05-27","cited_by_count":28,"area":"lr"},{"id":"2503.13881","title":"MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation","created":"2025-03-18","cited_by_count":28,"area":"lr"},{"id":"2501.08549","title":"The Devil is in Temporal Token: High Quality Video Reasoning Segmentation","created":"2025-01-15","cited_by_count":26,"area":"lr"},{"id":"2410.18923","title":"SegLLM: Multi-round Reasoning Segmentation","created":"2024-10-24","cited_by_count":25,"area":"lr"},{"id":"2504.00640","title":"POPEN: Preference-Based Optimization and Ensemble for LVLM-Based Reasoning Segmentation","created":"2025-04-01","cited_by_count":22,"area":"lr"},{"id":"2501.04670","title":"Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs","created":"2025-01-08","cited_by_count":16,"area":"lr"},{"id":"2407.04681","title":"Rethinking Visual Prompting for Multimodal Large Language Models with External Knowledge","created":"2024-07-05","cited_by_count":13,"area":"lr"},{"id":"2504.12795","title":"EarthGPT-X: A Spatial MLLM for Multi-level Multi-Source Remote Sensing Imagery Understanding with Visual Prompting","created":"2025-04-17","cited_by_count":11,"area":"lr"},{"id":"2507.00748","title":"Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning","created":"2025-07-01","cited_by_count":11,"area":"lr"},{"id":"2505.11852","title":"MedSG-Bench: A Benchmark for Medical Image Sequences Grounding","created":"2025-05-17","cited_by_count":8,"area":"lr"},{"id":"2602.06566","title":"SPARC: Separating Perception And Reasoning Circuits for Test-time Scaling of VLMs","created":"2026-02-06","cited_by_count":7,"area":"lr"},{"id":"2509.03501","title":"Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data","created":"2025-09-03","cited_by_count":6,"area":"lr"},{"id":"2603.03857","title":"DeepScan: A Training-Free Framework for Visually Grounded Reasoning in Large Vision-Language Models","created":"2026-03-04","cited_by_count":6,"area":"lr"},{"id":"2604.11789","title":"LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation","created":"2026-04-13","cited_by_count":6,"area":"lr"},{"id":"2510.06243","title":"CoT Referring: Improving Referring Expression Tasks with Grounded Reasoning","created":"2025-10-03","cited_by_count":5,"area":"lr"},{"id":"2407.14133","title":"I Know About \"Up\"! Enhancing Spatial Reasoning in Visual Language Models Through 3D Reconstruction","created":"2024-07-19","cited_by_count":4,"area":"lr"},{"id":"2506.07778","title":"A Neurosymbolic Agent System for Compositional Visual Reasoning","created":"2025-06-09","cited_by_count":4,"area":"lr"},{"id":"2510.09274","title":"MomentSeg: Moment-Centric Sampling for Enhanced Video Pixel Understanding","created":"2025-10-10","cited_by_count":4,"area":"lr"},{"id":"2602.03733","title":"RegionReasoner: Region-Grounded Multi-Round Visual Reasoning","created":"2026-02-03","cited_by_count":4,"area":"lr"},{"id":"2605.20676","title":"VISTAQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence","created":"2026-05-20","cited_by_count":4,"area":"lr"},{"id":"2608.20492","title":"Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs","created":"2026-08-20","cited_by_count":4,"area":"lr"},{"id":"2503.10225","title":"Unveiling the Invisible: Reasoning Complex Occlusions Amodally with AURA","created":"2025-03-13","cited_by_count":3,"area":"lr"},{"id":"2510.22118","title":"GRAID: Enhancing Spatial Reasoning of VLMs Through High-Fidelity Data Generation","created":"2025-10-25","cited_by_count":3,"area":"lr"},{"id":"2406.00872","title":"OLIVE: Object Level In-Context Visual Embeddings","created":"2024-06-02","cited_by_count":2,"area":"lr"},{"id":"2412.17741","title":"Reasoning to Attend: Try to Understand How <SEG> Token Works","created":"2024-12-23","cited_by_count":2,"area":"lr"},{"id":"2506.22880","title":"Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder","created":"2025-06-28","cited_by_count":2,"area":"lr"},{"id":"2603.12382","title":"SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs","created":"2026-03-12","cited_by_count":2,"area":"lr"},{"id":"2604.00270","title":"OmniSch: A Multimodal PCB Schematic Benchmark For Structured Diagram Visual Reasoning","created":"2026-03-31","cited_by_count":2,"area":"lr"},{"id":"2607.00115","title":"PixelEyes: Decoupling Perception and Reasoning for Pinpoint Visual Evidence Seeking","created":"2026-06-30","cited_by_count":2,"area":"lr"},{"id":"2412.14672","title":"FiVL: A Framework for Improved Vision-Language Alignment through the Lens of Training, Evaluation and Explainability","created":"2024-12-19","cited_by_count":1,"area":"lr"},{"id":"2602.19505","title":"Test-Time Computing for Referring Multimodal Large Language Models","created":"2026-02-23","cited_by_count":1,"area":"lr"},{"id":"2603.27060","title":"VIRST: Video-Instructed Reasoning Assistant for SpatioTemporal Segmentation","created":"2026-03-28","cited_by_count":1,"area":"lr"},{"id":"2606.00987","title":"An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation","created":"2026-05-31","cited_by_count":1,"area":"lr"},{"id":"2606.25701","title":"Falcon: Functional Assembly and Language for Compositional Reasoning in X-ray","created":"2026-06-24","cited_by_count":1,"area":"lr"},{"id":"2607.12319","title":"DM-KG: A Novel Method for Boosting Spatial Cognition of Vision-Language Models in Street View Imagery","created":"2026-07-14","cited_by_count":1,"area":"lr"},{"id":"2506.01795","title":"R2SM: Referring and Reasoning for Selective Masks","created":"2025-06-02","cited_by_count":0,"area":"lr"},{"id":"2512.11680","title":"Cross-modal Context-aware Learning for Visual Prompt Guided Multimodal Image Understanding in Remote Sensing","created":"2025-12-12","cited_by_count":0,"area":"lr"},{"id":"2605.13530","title":"Towards Unified Surgical Scene Understanding:Bridging Reasoning and Grounding via MLLMs","created":"2026-05-13","cited_by_count":0,"area":"lr"},{"id":"2605.15997","title":"Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning","created":"2026-05-15","cited_by_count":0,"area":"lr"},{"id":"2608.22885","title":"DRAgent: Discriminative Reasoning Agent for Referring Expression Segmentation","created":"2026-08-24","cited_by_count":0,"area":"lr"},{"id":"2608.24574","title":"PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos","created":"2026-08-25","cited_by_count":0,"area":"lr"},{"id":"2608.28707","title":"ReVA: A Region-Aware Visual Assistant for Visually Grounded Question Answering","created":"2026-08-27","cited_by_count":0,"area":"lr"},{"id":"2608.30758","title":"CheXGround: Anatomical Region Tokens for Grounded Longitudinal Chest X-ray Interpretation","created":"2026-08-31","cited_by_count":0,"area":"lr"},{"id":"2609.20235","title":"Scene-Q: Confidence-Aware Coarse-to-Fine Querying of 3D Scenes with Selective VLM Reasoning","created":"2026-07-28","cited_by_count":0,"area":"lr"},{"id":"2609.30783","title":"Skip the Talk, Re-Focus on Vision: Latent Reasoning for Reasoning Segmentation in Multimodal Large Language Models","created":"2026-09-25","cited_by_count":0,"area":"lr"},{"id":"2609.37374","title":"MG-Thinker: Bi-Axial Self-Reflection for Multi-Image Reasoning Grounding","created":"2026-09-29","cited_by_count":0,"area":"lr"},{"id":"2610.20083","title":"VisualWorldBench: A Fine-Grained Multi-Task Benchmark for Evaluating Visual World Knowledge in MLLMs","created":"2026-10-14","cited_by_count":0,"area":"lr"}],"next_cursor":null}