3 citations · 6 across the 13 of their papers we have counts for
16 papers
Role-aware Heuristic Episodic Attention for Conversational LLMs
Wanyang Hong, Zhaoning Zhang, Yi Chen +5
Large language models often lose track of persistent instructions and relevant information as multi-turn conversations grow. We study this cumulative contextual decay through three…
Making Foresight Actionable: Repurposing Representation Alignment in World Action Models
Lu Qiu, Yizhuo Li, Yi Chen +3
World Action Models (WAMs) offer a promising route for robot manipulation by using video generation models to model future scene evolution before producing control actions. However…
DIAL: Decoupling Intent and Action via Latent World Modeling for End-to-End VLA
Yi Chen, Yuying Ge, Hui Zhou +3
The development of Vision-Language-Action (VLA) models has been significantly accelerated by pre-trained Vision-Language Models (VLMs). However, most existing end-to-end VLAs treat…
UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling
Boyu Chen, Yi Chen, Lu Qiu +3
Scaling humanoid foundation models is bottlenecked by the scarcity of robotic data. While massive egocentric human data offers a scalable alternative, bridging the cross-embodiment…
POP: Online Structural Pruning Enables Efficient Inference of Large Foundation Models
Yi Chen, Wonjin Shin, Shuhong Liu +6
Large foundation models (LFMs) achieve strong performance through scaling, yet current structural pruning methods derive fixed pruning decisions during inference, overlooking spars…
Role-aware Heuristic Episodic Attention for Conversational LLMs
Wanyang Hong, Zhaoning Zhang, Yi Chen +5
Large language models often lose track of persistent instructions and relevant information as multi-turn conversations grow. We study this cumulative contextual decay through three…
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…
GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
Tianchen Deng, Xuefeng Chen, Yi Chen +8
Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding capabilities and can only genera…
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…
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…
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…
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…
EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios
Lu Qiu, Yi Chen, Yuying Ge +3
The advent of Multimodal Large Language Models, leveraging the power of Large Language Models, has recently demonstrated superior multimodal understanding and reasoning abilities,…
Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos
Yi Chen, Yuying Ge, Weiliang Tang +5
Recent developments in Large Language Models pre-trained on extensive corpora have shown significant success in various natural language processing tasks with minimal fine-tuning.…
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Bohao Li, Yuying Ge, Yi Chen +3
Comprehending text-rich visual content is paramount for the practical application of Multimodal Large Language Models (MLLMs), since text-rich scenarios are ubiquitous in the real…
EgoPlan-Bench: Benchmarking Multimodal Large Language Models for Human-Level Planning
Yi Chen, Yuying Ge, Yixiao Ge +6
The pursuit of artificial general intelligence (AGI) has been accelerated by Multimodal Large Language Models (MLLMs), which exhibit superior reasoning, generalization capabilities…