{"total":29,"rows":[{"id":"2410.19702","title":"TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning","created":"2024-10-25","cited_by_count":106,"area":"mllm"},{"id":"2406.16338","title":"VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models","created":"2024-06-24","cited_by_count":90,"area":"mllm"},{"id":"2412.19326","title":"Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment","created":"2024-12-26","cited_by_count":29,"area":"mllm"},{"id":"2501.13919","title":"Temporal Preference Optimization for Long-Form Video Understanding","created":"2025-01-23","cited_by_count":29,"area":"mllm"},{"id":"2403.16998","title":"Understanding Long Videos with Multimodal Language Models","created":"2024-03-25","cited_by_count":25,"area":"mllm"},{"id":"2503.08221","title":"EgoBlind: Towards Egocentric Visual Assistance for the Blind","created":"2025-03-11","cited_by_count":21,"area":"mllm"},{"id":"2508.10922","title":"A Survey on Video Temporal Grounding with Multimodal Large Language Model","created":"2025-08-07","cited_by_count":20,"area":"mllm"},{"id":"2406.18113","title":"Chrono: A Simple Blueprint for Representing Time in MLLMs","created":"2024-06-26","cited_by_count":18,"area":"mllm"},{"id":"2505.20715","title":"MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding","created":"2025-05-27","cited_by_count":12,"area":"mllm"},{"id":"2510.17023","title":"Enrich and Detect: Video Temporal Grounding with Multimodal LLMs","created":"2025-10-19","cited_by_count":12,"area":"mllm"},{"id":"2505.24158","title":"Threading Keyframe with Narratives: MLLMs as Strong Long Video Comprehenders","created":"2025-05-30","cited_by_count":10,"area":"mllm"},{"id":"2501.19164","title":"Poison as Cure: Visual Noise for Mitigating Object Hallucinations in LVMs","created":"2025-01-31","cited_by_count":9,"area":"mllm"},{"id":"2509.15178","title":"Unleashing the Potential of Multimodal LLMs for Zero-Shot Spatio-Temporal Video Grounding","created":"2025-09-18","cited_by_count":9,"area":"mllm"},{"id":"2512.03963","title":"TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning","created":"2025-12-03","cited_by_count":8,"area":"mllm"},{"id":"2503.19356","title":"Can Vision-Language Models Answer Face to Face Questions in the Real-World?","created":"2025-03-25","cited_by_count":7,"area":"mllm"},{"id":"2509.11862","title":"Bridging Vision Language Models and Symbolic Grounding for Video Question Answering","created":"2025-09-15","cited_by_count":4,"area":"mllm"},{"id":"2604.08966","title":"How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms","created":"2026-04-10","cited_by_count":3,"area":"mllm"},{"id":"2506.16112","title":"AutoV: Loss-Oriented Ranking for Visual Prompt Retrieval in LVLMs","created":"2025-06-19","cited_by_count":2,"area":"mllm"},{"id":"2512.11336","title":"UFVideo: Towards Unified Fine-Grained Video Cooperative Understanding with Large Language Models","created":"2025-12-12","cited_by_count":2,"area":"mllm"},{"id":"2505.05318","title":"Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects","created":"2025-05-08","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":"2605.09422","title":"Perception Without Engagement: Dissecting the Causal Discovery Deficit in LMMs","created":"2026-05-10","cited_by_count":1,"area":"mllm"},{"id":"2511.02182","title":"Pinpointing Trigger Moment for Grounded Video QA: Enhancing Spatio-temporal Grounding in Multimodal Large Language Models","created":"2025-11-04","cited_by_count":0,"area":"mllm"},{"id":"2511.13458","title":"Trust in Vision-Language Models: Insights from a Participatory User Workshop","created":"2025-11-17","cited_by_count":0,"area":"mllm"},{"id":"2603.11689","title":"Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks","created":"2026-03-12","cited_by_count":0,"area":"mllm"},{"id":"2605.19223","title":"HAVEN: Hierarchically Aligned Multimodal Benchmark for Unified Video Understanding","created":"2026-05-19","cited_by_count":0,"area":"mllm"},{"id":"2606.30288","title":"VisReflect: Latent Visual Reflection for Fine-Grained Perception in Long Visual Context","created":"2026-06-29","cited_by_count":0,"area":"mllm"},{"id":"2607.02269","title":"AnyGroundBench: A Specialized-Domain Benchmark for Video Grounding in Vision-Language Models","created":"2026-07-02","cited_by_count":0,"area":"mllm"},{"id":"2609.02000","title":"Who Drives the Probability Game of VLMs? A Temporal Causal Drive Evaluation Framework","created":"2026-09-02","cited_by_count":0,"area":"mllm"}],"next_cursor":null}