activity
20232026
most citedSEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

3 citations · 6 across the 12 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CL2025

Rhea: Role-aware Heuristic Episodic Attention for Conversational LLMs

Wanyang Hong, Zhaoning Zhang, Yi Chen +5

Large Language Models (LLMs) have achieved remarkable performance on single-turn tasks, yet their effectiveness deteriorates in multi-turn conversations. We define this phenomenon…

cs.RO2025

RANGER: A Monocular Zero-Shot Semantic Navigation Framework through Visual Contextual Adaptation

Ming-Ming Yu, Yi Chen, Börje F. Karlsson +1

Efficient target localization and autonomous navigation in complex environments are fundamental to real-world embodied applications. While recent advances in multimodal foundation…

cs.CV2025

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…

cs.AI20253 cited

A Survey on Collaborative Mechanisms Between Large and Small Language Models

Yi Chen, JiaHao Zhao, HaoHao Han

Large Language Models (LLMs) deliver powerful AI capabilities but face deployment challenges due to high resource costs and latency, whereas Small Language Models (SLMs) offer effi…

cs.CV2025

SN-LiDAR: Semantic Neural Fields for Novel Space-time View LiDAR Synthesis

Yi Chen, Tianchen Deng, Wentao Zhao +4

Recent research has begun exploring novel view synthesis (NVS) for LiDAR point clouds, aiming to generate realistic LiDAR scans from unseen viewpoints. However, most existing appro…

cs.CV2025

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…