activity
20212026
most citedWhen Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities

338 citations · 367 across the 22 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Skill-RM: Unifying Heterogeneous Evaluation Criteria via Agent Skill

Tao Chen, Gangwei Jiang, Pengyu Cheng +10

Reward models (RMs) provide critical feedback signals for LLM post-training, notably in reinforced fine-tuning (RFT) and reinforcement learning (RL) pipelines. However, current rew…

cs.LG2025

Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning

Gangwei Jiang, Caigao Jiang, Zhaoyi Li +5

Catastrophic forgetting (CF) poses a significant challenge in machine learning, where a model forgets previously learned information upon learning new tasks. Despite the advanced c…

cs.LG2025

GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series Data

Cheng He, Xu Huang, Gangwei Jiang +7

Despite recent progress in time-series foundation models, challenges persist in improving representation learning and adapting to diverse downstream tasks. We introduce a General T…

cs.LG2023★ 3 cited

Prompt-augmented Temporal Point Process for Streaming Event Sequence

Siqiao Xue, Yan Wang, Zhixuan Chu +7

Neural Temporal Point Processes (TPPs) are the prevalent paradigm for modeling continuous-time event sequences, such as user activities on the web and financial transactions. In re…

cs.LG2023★ 4 cited

Continual Learning in Predictive Autoscaling

Hongyan Hao, Zhixuan Chu, Shiyi Zhu +7

Predictive Autoscaling is used to forecast the workloads of servers and prepare the resources in advance to ensure service level objectives (SLOs) in dynamic cloud environments. Ho…