4 papers · 1 filter
Distributionally Robust Token Optimization in RLHF
Yeping Jin, Jiaming Hu, Ioannis Ch. Paschalidis
Large Language Models (LLMs) tend to respond correctly to prompts that align well with the data they were trained and fine-tuned on. Yet, small shifts in wording, format, or langua…
Towards General Preference Alignment: Diffusion Models at Nash Equilibrium
Jiaming Hu, Jiamu Bai, Haoyu Wang +2
Reinforcement learning from human feedback (RLHF) has been popular for aligning text-to-image (T2I) diffusion models with human preferences. As a mainstream branch of RLHF, Direct…
Bridging the Gap Between Average and Discounted TD Learning
Haoxing Tian, Zaiwei Chen, Ioannis Ch. Paschalidis +1
The analysis of Temporal Difference (TD) learning in the average-reward setting faces notable theoretical difficulties because the Bellman operator is not contractive with respect…
Distributionally Robust Learning in Survival Analysis
Yeping Jin, Lauren Wise, Ioannis Ch. Paschalidis
We introduce an innovative approach that incorporates a Distributionally Robust Learning (DRL) approach into Cox regression to enhance the robustness and accuracy of survival predi…