44 citations · 127 across the 23 of their papers we have counts for
23 papers · 1 filter
Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
Chuanqi Cheng, Jian Guan, Wei Wu +1
Long-form video processing fundamentally challenges vision-language models (VLMs) due to the high computational costs of handling extended temporal sequences. Existing token prunin…
PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Models
Xueliang Zhao, Wei Wu, Jian Guan +1
The ability of large language models to solve complex mathematical problems has progressed significantly, particularly for tasks requiring advanced reasoning. However, the scarcity…
A Survey on Personalized Alignment -- The Missing Piece for Large Language Models in Real-World Applications
Jian Guan, Junfei Wu, Jia-Nan Li +2
Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their transition to real-world applications reveals a critical limitation: the inability to adapt to ind…
From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignment
Jia-Nan Li, Jian Guan, Songhao Wu +2
Large language models (LLMs) have traditionally been aligned through one-size-fits-all approaches that assume uniform human preferences, fundamentally overlooking the diversity in…
2D-TPE: Two-Dimensional Positional Encoding Enhances Table Understanding for Large Language Models
Jia-Nan Li, Jian Guan, Wei Wu +2
Tables are ubiquitous across various domains for concisely representing structured information. Empowering large language models (LLMs) to reason over tabular data represents an ac…
Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form Planning
Jiaxin Wen, Jian Guan, Hongning Wang +2
Despite the remarkable success of large language models (LLMs) on traditional natural language processing tasks, their planning ability remains a critical bottleneck in tackling co…