161 citations · 387 across the 61 of their papers we have counts for
7 papers · 1 filter
VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs
Wensi Huang, Shaohao Zhu, Meng Wei +7
In most existing embodied navigation tasks, instructions are well-defined and unambiguous, such as instruction following and object searching. Under this idealized setting, agents…
OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes
Yukun Huang, Jiwen Yu, Yanning Zhou +4
There are two prevalent ways for automatic 3D scene construction: procedural generation and 2D lifting. Among these, panorama-based 2D lifting has emerged as a promising technique,…
SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models
Weiyang Jin, Yuwei Niu, Jiaqi Liao +4
Recently, remarkable progress has been made in Unified Multimodal Models (UMMs), which integrate vision-language generation and understanding capabilities within a single framework…
StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling
Meng Wei, Chenyang Wan, Xiqian Yu +9
Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low latency grounded in language instruct…
GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning
Yi Chen, Yuying Ge, Rui Wang +4
Recent reinforcement learning approaches, such as outcome-supervised GRPO, have advanced Chain-of-Thought reasoning in large language models (LLMs), yet their adaptation to multimo…
AnimeShooter: A Multi-Shot Animation Dataset for Reference-Guided Video Generation
Lu Qiu, Yizhuo Li, Yuying Ge +3
Recent advances in AI-generated content (AIGC) have significantly accelerated animation production. To produce engaging animations, it is essential to generate coherent multi-shot…
Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1
Yi Chen, Yuying Ge, Rui Wang +4
Recent advancements in Chain of Thought (COT) generation have significantly improved the reasoning capabilities of Large Language Models (LLMs), with reinforcement learning (RL) em…