{"total":59,"rows":[{"id":"2412.04467","title":"VisionZip: Longer is Better but Not Necessary in Vision Language Models","created":"2024-12-05","cited_by_count":313,"area":"mllm"},{"id":"2506.22139","title":"Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs","created":"2025-06-27","cited_by_count":80,"area":"mllm"},{"id":"2405.16640","title":"A Survey of Multimodal Large Language Model from A Data-centric Perspective","created":"2024-05-26","cited_by_count":75,"area":"mllm"},{"id":"2406.11303","title":"VideoVista: A Versatile Benchmark for Video Understanding and Reasoning","created":"2024-06-17","cited_by_count":72,"area":"mllm"},{"id":"2412.03735","title":"VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding","created":"2024-12-04","cited_by_count":68,"area":"mllm"},{"id":"2412.18108","title":"Unveiling Visual Perception in Language Models: An Attention Head Analysis Approach","created":"2024-12-24","cited_by_count":35,"area":"mllm"},{"id":"2505.01481","title":"VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding","created":"2025-05-02","cited_by_count":32,"area":"mllm"},{"id":"2410.09733","title":"MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models","created":"2024-10-13","cited_by_count":31,"area":"mllm"},{"id":"2506.05332","title":"Unleashing Hour-Scale Video Training for Long Video-Language Understanding","created":"2025-06-05","cited_by_count":23,"area":"mllm"},{"id":"2510.00515","title":"Efficient Multi-modal Large Language Models via Progressive Consistency Distillation","created":"2025-10-01","cited_by_count":22,"area":"mllm"},{"id":"2406.14129","title":"Towards Event-oriented Long Video Understanding","created":"2024-06-20","cited_by_count":21,"area":"mllm"},{"id":"2510.23603","title":"PixelRefer: A Unified Framework for Spatio-Temporal Object Referring with Arbitrary Granularity","created":"2025-10-27","cited_by_count":21,"area":"mllm"},{"id":"2409.18991","title":"Surveying the MLLM Landscape: A Meta-Review of Current Surveys","created":"2024-09-17","cited_by_count":20,"area":"mllm"},{"id":"2411.10979","title":"VidComposition: Can MLLMs Analyze Compositions in Compiled Videos?","created":"2024-11-17","cited_by_count":18,"area":"mllm"},{"id":"2505.24867","title":"Time Blindness: Why Video-Language Models Can't See What Humans Can?","created":"2025-05-30","cited_by_count":18,"area":"mllm"},{"id":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"id":"2509.18056","title":"TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs","created":"2025-09-22","cited_by_count":15,"area":"mllm"},{"id":"2411.14401","title":"Beyond Training: Dynamic Token Merging for Zero-Shot Video Understanding","created":"2024-11-21","cited_by_count":13,"area":"mllm"},{"id":"2507.00469","title":"Bisecle: Binding and Separation in Continual Learning for Video Language Understanding","created":"2025-07-01","cited_by_count":13,"area":"mllm"},{"id":"2412.17574","title":"HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks","created":"2024-12-23","cited_by_count":11,"area":"mllm"},{"id":"2406.10484","title":"Beyond Raw Videos: Understanding Edited Videos with Large Multimodal Model","created":"2024-06-15","cited_by_count":10,"area":"mllm"},{"id":"2409.14993","title":"Multi-modal Generative AI: Multi-modal LLMs, Diffusions, and the Unification","created":"2024-09-23","cited_by_count":8,"area":"mllm"},{"id":"2602.16412","title":"ReMoRa: Multimodal Large Language Model based on Refined Motion Representation for Long-Video Understanding","created":"2026-02-18","cited_by_count":8,"area":"mllm"},{"id":"2503.08561","title":"ComicsPAP: understanding comic strips by picking the correct panel","created":"2025-03-11","cited_by_count":5,"area":"mllm"},{"id":"2509.00357","title":"SurgLLM: A Versatile Large Multimodal Model with Spatial Focus and Temporal Awareness for Surgical Video Understanding","created":"2025-08-30","cited_by_count":5,"area":"mllm"},{"id":"2604.05117","title":"Watch Before You Answer: Learning from Visually Grounded Post-Training","created":"2026-04-06","cited_by_count":5,"area":"mllm"},{"id":"2606.05843","title":"Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads","created":"2026-06-04","cited_by_count":4,"area":"mllm"},{"id":"2502.14882","title":"CalibQuant: 1-Bit KV Cache Quantization for Multimodal LLMs","created":"2025-02-15","cited_by_count":3,"area":"mllm"},{"id":"2511.17945","title":"Test-Time Temporal Sampling for Efficient MLLM Video Understanding","created":"2025-11-22","cited_by_count":3,"area":"mllm"},{"id":"2602.03230","title":"EventFlash: Towards Efficient MLLMs for Event-Based Vision","created":"2026-02-03","cited_by_count":3,"area":"mllm"},{"id":"2603.13119","title":"Geometry-Guided Camera Motion Understanding in VideoLLMs","created":"2026-03-13","cited_by_count":3,"area":"mllm"},{"id":"2605.07299","title":"EgoPro-Bench: Benchmarking Personalized Proactive Interaction in Egocentric Video Streams","created":"2026-05-08","cited_by_count":3,"area":"mllm"},{"id":"2503.14161","title":"CoSpace: Benchmarking Continuous Space Perception Ability for Vision-Language Models","created":"2025-03-18","cited_by_count":2,"area":"mllm"},{"id":"2602.08861","title":"TiFRe: Text-guided Video Frame Reduction for Efficient Video Multi-modal Large Language Models","created":"2026-02-09","cited_by_count":2,"area":"mllm"},{"id":"2607.25125","title":"LENS: Adaptive Spatio-Temporal Zooming for Keyframe Sampling in Long-Form Videos","created":"2026-07-27","cited_by_count":2,"area":"mllm"},{"id":"2506.12336","title":"Benchmarking the Trustworthiness in Multimodal LLMs for Video Understanding","created":"2025-06-14","cited_by_count":1,"area":"mllm"},{"id":"2507.02946","title":"Iterative Zoom-In: Temporal Interval Exploration for Long Video Understanding","created":"2025-06-28","cited_by_count":1,"area":"mllm"},{"id":"2602.00559","title":"Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models","created":"2026-01-31","cited_by_count":1,"area":"mllm"},{"id":"2604.02093","title":"GroundVTS: Visual Token Sampling in Multimodal Large Language Models for Video Temporal Grounding","created":"2026-04-02","cited_by_count":1,"area":"mllm"},{"id":"2604.11240","title":"Decoupled Similarity for Task-Aware Token Pruning in Large Vision-Language Models","created":"2026-04-13","cited_by_count":1,"area":"mllm"},{"id":"2605.31598","title":"Linear Scaling Video VLMs for Long Video Understanding","created":"2026-05-29","cited_by_count":1,"area":"mllm"},{"id":"2608.10949","title":"StreamFlow: Dynamic Memory Flows for Streaming Video Understanding","created":"2026-08-11","cited_by_count":1,"area":"mllm"},{"id":"2507.17050","title":"Toward Scalable Video Narration: A Training-free Approach Using Multimodal Large Language Models","created":"2025-07-22","cited_by_count":0,"area":"mllm"},{"id":"2511.20162","title":"Action Without Interaction: Probing the Physical Foundations of Video LMMs via Contact-Release Detection","created":"2025-11-25","cited_by_count":0,"area":"mllm"},{"id":"2602.18540","title":"Rodent-Bench","created":"2026-02-20","cited_by_count":0,"area":"mllm"},{"id":"2604.08050","title":"ABMAMBA: Multimodal Large Language Model with Aligned Hierarchical Bidirectional Scan for Efficient Video Captioning","created":"2026-04-09","cited_by_count":0,"area":"mllm"},{"id":"2604.12335","title":"SynMulti: Synthetic-to-Real Learning for Multimodal Video Understanding","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2604.17375","title":"When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models","created":"2026-04-19","cited_by_count":0,"area":"mllm"},{"id":"2605.08974","title":"Tracking the Truth: Object-Centric Spatio-Temporal Monitoring for Video Large Language Models","created":"2026-05-09","cited_by_count":0,"area":"mllm"},{"id":"2605.13375","title":"GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models","created":"2026-05-13","cited_by_count":0,"area":"mllm"},{"id":"2605.20211","title":"Leveraging Vision-Language Models to Detect Attention in Educational Videos","created":"2026-04-20","cited_by_count":0,"area":"mllm"},{"id":"2605.20950","title":"Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models","created":"2026-05-20","cited_by_count":0,"area":"mllm"},{"id":"2606.11792","title":"MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models","created":"2026-06-10","cited_by_count":0,"area":"mllm"},{"id":"2606.19062","title":"DREAM: Extending Vision-Language Models with Dual-Objective Encoding for Cross-Modal Retrieval","created":"2026-06-17","cited_by_count":0,"area":"mllm"},{"id":"2606.29445","title":"Bridging VideoQA and Video-Guided Agentic Tasks via Generalized Keyframe Extraction","created":"2026-06-28","cited_by_count":0,"area":"mllm"},{"id":"2607.21022","title":"ProCap: Prominence-guided Object Rectification for Faithful and Comprehensive Video Captioning","created":"2026-07-23","cited_by_count":0,"area":"mllm"},{"id":"2609.29607","title":"STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models","created":"2026-08-28","cited_by_count":0,"area":"mllm"},{"id":"2609.31697","title":"Video Captioning in Low-Light Conditions through Efficient Uncertainty-Aware Caption Correction","created":"2026-09-18","cited_by_count":0,"area":"mllm"},{"id":"2610.00196","title":"GPEC: Efficient Pre-LLM Gaussian Process Embedding Correction for Cardiac Video Caption Generation","created":"2026-09-18","cited_by_count":0,"area":"mllm"}],"next_cursor":null}