papers
Publications (3)
cs.CL2021
MAVE: A Product Dataset for Multi-source Attribute Value Extraction
Li Yang, Qifan Wang, Zac Yu +5
Attribute value extraction refers to the task of identifying values of an attribute of interest from product information. Product attribute values are essential in many e-commerce…
cs.LG2024
Parameter Efficient Reinforcement Learning from Human Feedback
Hakim Sidahmed, Samrat Phatale, Alex Hutcheson +16
While Reinforcement Learning from Human Feedback (RLHF) effectively aligns pretrained Large Language and Vision-Language Models (LLMs, and VLMs) with human preferences, its computa…
cs.CL2025
Improving Neutral Point-of-View Generation with Data- and Parameter-Efficient RL
Jessica Hoffmann, Christiane Ahlheim, Zac Yu +8
The paper shows that parameter-efficient reinforcement learning (PE-RL) is a highly effective training regime to improve large language models' (LLMs) ability to answer queries on…