3 citations · 7 across the 8 of their papers we have counts for
11 papers
Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning
Xuanyu Lei, Chenliang Li, Yuning Wu +7
Recent advances in Large Language Models(LLMs) have enabled strong performance in long-form writing, but current training paradigms remain limited: Supervised Fine-Tuning (SFT) rem…
Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration
Zijun Liu, Zhennan Wan, Peng Li +3
With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large quantity of retrieved knowledge t…
MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding
Fuwen Luo, Shengfeng Lou, Chi Chen +9
Video temporal understanding is crucial for multimodal large language models (MLLMs) to reason over events in videos. Despite recent advances in general video understanding, curren…
AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient Optimization
Yiyang Du, Xiaochen Wang, Chi Chen +9
Recently, model merging methods have demonstrated powerful strengths in combining abilities on various tasks from multiple Large Language Models (LLMs). While previous model mergin…
ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy
Zonghan Yang, Peng Li, Ming Yan +3
Language agents have demonstrated autonomous decision-making abilities by reasoning with foundation models. Recently, efforts have been made to train language agents for performanc…
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching
Mieradilijiang Maimaiti, Yuanhang Zheng, Ji Zhang +3
Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-cus…
Budget-Constrained Tool Learning with Planning
Yuanhang Zheng, Peng Li, Ming Yan +3
Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, ha…
PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs
An Liu, Zonghan Yang, Zhenhe Zhang +6
While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-sp…
Model Composition for Multimodal Large Language Models
Chi Chen, Yiyang Du, Zheng Fang +8
Recent developments in Multimodal Large Language Models (MLLMs) have shown rapid progress, moving towards the goal of creating versatile MLLMs that understand inputs from various m…
Browse and Concentrate: Comprehending Multimodal Content via prior-LLM Context Fusion
Ziyue Wang, Chi Chen, Yiqi Zhu +7
With the bloom of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) that incorporate LLMs with pre-trained vision models have recently demonstrated impressive…
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking
Zijun Liu, Boqun Kou, Peng Li +4
Despite the strong performance of large language models (LLMs) across a wide range of tasks, they still have reliability issues. Previous studies indicate that strong LLMs like GPT…