8 papers
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
Jia-Nan Li, Jian Guan, Wei Wu +1
Autoregressive models (ARMs) are hindered by slow sequential inference. While masked diffusion models (MDMs) offer a parallel alternative, they suffer from critical drawbacks: high…
Text as a Universal Interface for Transferable Personalization
Yuting Liu, Jian Guan, Jia-Nan Li +4
We study the problem of personalization in large language models (LLMs). Prior work predominantly represents user preferences as implicit, model-specific vectors or parameters, yie…
Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals
Jia-Nan Li, Jian Guan, Wei Wu +1
Large language models (LLMs) have demonstrated significant success in complex reasoning tasks such as math and coding. In contrast to these tasks where deductive reasoning predomin…
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…
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…
StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
Jia-Nan Li, Quan Tu, Cunli Mao +3
Standard Large Language Models (LLMs) struggle with handling dialogues with long contexts due to efficiency and consistency issues. According to our observation, dialogue contexts…