2 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
Exploring Forum Post Retrieval with Generative Modeling
Yang Li, Yaguang Liu, Heng Liu +14
Generative recommendation (GR) has emerged as an alternative to embedding-based retrieval, building on the success of generative models in language and vision. We are exploring GR…
Towards Reliable, Generalizable, and Specific In-Context Knowledge Editing via Multi-Objective Reinforcement Learning
Xuzhong Wang, Maiqi Jiang, Tejal Nair +3
Large Language Models (LLMs) are powerful but limited by static parametric knowledge that becomes outdated once pretraining ends. Knowledge editing addresses this problem by updati…
Speculative Sampling with Reinforcement Learning
Chenan Wang, Daniel H. Shi, Haipeng Chen
Inference time latency has remained an open challenge for real world applications of large language models (LLMs). State-of-the-art (SOTA) speculative sampling (SpS) methods for LL…
DIP: Dynamic In-Context Planner For Diffusion Language Models
Yang Li, Han Meng, Chenan Wang +3
Diffusion language models (DLMs) have shown strong potential for general natural language tasks with in-context examples. Existing In-Context Learning (ICL) approaches largely inhe…