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20242026
most citedSlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

4 citations · 8 across the 9 of their papers we have counts for

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cs.CV2025

Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction

Kaisi Guan, Xihua Wang, Zhengfeng Lai +5

This study focuses on a challenging yet promising task, Text-to-Sounding-Video (T2SV) generation, which aims to generate a video with synchronized audio from text conditions, meanw…

cs.CV2025

Breaking Down Video LLM Benchmarks: Knowledge, Spatial Perception, or True Temporal Understanding?

Bo Feng, Zhengfeng Lai, Shiyu Li +4

Existing video understanding benchmarks often conflate knowledge-based and purely image-based questions, rather than clearly isolating a model's temporal reasoning ability, which i…

cs.CV2025

StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant

Haibo Wang, Bo Feng, Zhengfeng Lai +6

We present StreamBridge, a simple yet effective framework that seamlessly transforms offline Video-LLMs into streaming-capable models. It addresses two fundamental challenges in ad…

cs.CV2025

SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding

Mingze Xu, Mingfei Gao, Shiyu Li +7

We introduce SlowFast-LLaVA-1.5 (abbreviated as SF-LLaVA-1.5), a family of video large language models (LLMs) offering a token-efficient solution for long-form video understanding.…

cs.CV2025

ETVA: Evaluation of Text-to-Video Alignment via Fine-grained Question Generation and Answering

Kaisi Guan, Zhengfeng Lai, Yuchong Sun +5

Precisely evaluating semantic alignment between text prompts and generated videos remains a challenge in Text-to-Video (T2V) Generation. Existing text-to-video alignment metrics li…