activity
20182025
most citedModel-Based Reinforcement Learning with Adversarial Training for Online Recommendation

44 citations · 143 across the 30 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.LG2025

Trust-Region Adaptive Policy Optimization

Mingyu Su, Jian Guan, Yuxian Gu +2

Post-training methods, especially Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), play an important role in improving large language models' (LLMs) complex reasoning…

cs.CL2025

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…

cs.CL2025★ 4 cited

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…

cs.CL2025

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…

cs.CL2025

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…

cs.LG2025

Theoretical Benefit and Limitation of Diffusion Language Model

Guhao Feng, Yihan Geng, Jian Guan +3

Diffusion language models have emerged as a promising approach for text generation. One would naturally expect this method to be an efficient replacement for autoregressive models…

cs.AI2025★ 6 cited

Human Decision-making is Susceptible to AI-driven Manipulation

Sahand Sabour, June M. Liu, Siyang Liu +13

AI systems are increasingly intertwined with daily life, assisting users with various tasks and guiding decision-making. This integration introduces risks of AI-driven manipulation…