{"total":18,"rows":[{"id":"2504.07086","title":"A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility","created":"2025-04-09","cited_by_count":93,"area":"lr"},{"id":"2510.27492","title":"ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning","created":"2025-10-30","cited_by_count":56,"area":"lr"},{"id":"2510.25760","title":"Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarks","created":"2025-10-29","cited_by_count":33,"area":"lr"},{"id":"2508.17298","title":"Explain Before You Answer: A Survey on Compositional Visual Reasoning","created":"2025-08-24","cited_by_count":28,"area":"lr"},{"id":"2509.25373","title":"From Perception to Cognition: A Survey of Vision-Language Interactive Reasoning in Multimodal Large Language Models","created":"2025-09-29","cited_by_count":26,"area":"lr"},{"id":"2509.24322","title":"Multimodal Large Language Models Meet Multimodal Emotion Recognition and Reasoning: A Survey","created":"2025-09-29","cited_by_count":19,"area":"lr"},{"id":"2505.18536","title":"Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models","created":"2025-05-24","cited_by_count":14,"area":"lr"},{"id":"2505.14404","title":"ViC-Bench: Benchmarking Visual-Interleaved Chain-of-Thought Capability in MLLMs with Free-Style Intermediate State Representations","created":"2025-05-20","cited_by_count":12,"area":"lr"},{"id":"2507.03483","title":"BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset","created":"2025-07-04","cited_by_count":12,"area":"lr"},{"id":"2505.15472","title":"PhysicsArena: The First Multimodal Physics Reasoning Benchmark Exploring Variable, Process, and Solution Dimensions","created":"2025-05-21","cited_by_count":9,"area":"lr"},{"id":"2510.09361","title":"BLINK-Twice: You see, but do you observe? A Reasoning Benchmark on Visual Perception","created":"2025-10-10","cited_by_count":9,"area":"lr"},{"id":"2512.04563","title":"COOPER: A Unified Model for Cooperative Perception and Reasoning in Spatial Intelligence","created":"2025-12-04","cited_by_count":9,"area":"lr"},{"id":"2602.23306","title":"ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding","created":"2026-02-26","cited_by_count":7,"area":"lr"},{"id":"2604.00558","title":"STAR: Mitigating Cascading Errors in Spatial Reasoning via Turn-point Alignment and Segment-level DPO","created":"2026-04-01","cited_by_count":4,"area":"lr"},{"id":"2510.06292","title":"ChainMPQ: Interleaved Text-Image Reasoning Chains for Mitigating Relation Hallucinations","created":"2025-10-07","cited_by_count":1,"area":"lr"},{"id":"2511.12861","title":"From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models","created":"2025-11-17","cited_by_count":1,"area":"lr"},{"id":"2603.08369","title":"M$^3$-ACE: Rectifying Visual Perception in Multimodal Math Reasoning via Multi-Agentic Context Engineering","created":"2026-03-09","cited_by_count":1,"area":"lr"},{"id":"2603.18656","title":"Balanced Thinking: Improving Chain of Thought Training in Vision Language Models","created":"2026-03-19","cited_by_count":1,"area":"lr"}],"next_cursor":null}