1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CL2025★ 1 cited
GRACE: Generative Representation Learning via Contrastive Policy Optimization
Jiashuo Sun, Shixuan Liu, Zhaochen Su +6
Prevailing methods for training Large Language Models (LLMs) as text encoders rely on contrastive losses that treat the model as a black box function, discarding its generative and…
cs.CL2025
Precise Information Control in Long-Form Text Generation
Jacqueline He, Howard Yen, Margaret Li +7
A central challenge in language models (LMs) is faithfulness hallucination: the generation of information unsubstantiated by input context. To study this problem, we propose Precis…
cs.CL2024
Predicting vs. Acting: A Trade-off Between World Modeling & Agent Modeling
Margaret Li, Weijia Shi, Artidoro Pagnoni +2
RLHF-aligned LMs have shown unprecedented ability on both benchmarks and long-form text generation, yet they struggle with one foundational task: next-token prediction. As RLHF mod…