2 citations · 4 across the 2 of their papers we have counts for
4 papers
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
Tianci Liu, Ruirui Li, Yunzhe Qi +8
Large language models (LLMs) have achieved remarkable performance on various natural language tasks. However, they are trained on static corpora and their knowledge can become outd…
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
Yilun Jin, Zheng Li, Chenwei Zhang +19
Online shopping is a complex multi-task, few-shot learning problem with a wide and evolving range of entities, relations, and tasks. However, existing models and benchmarks are com…
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
Tianxin Wei, Bowen Jin, Ruirui Li +8
Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration. Ou…
Two-Step Offline Preference-Based Reinforcement Learning with Constrained Actions
Yinglun Xu, Tarun Suresh, Rohan Gumaste +10
Preference-based reinforcement learning (PBRL) in the offline setting has succeeded greatly in industrial applications such as chatbots. A two-step learning framework where one app…