4 citations · 10 across the 6 of their papers we have counts for
6 papers
Risk-Averse Finetuning of Large Language Models
Sapana Chaudhary, Ujwal Dinesha, Dileep Kalathil +1
We consider the challenge of mitigating the generation of negative or toxic content by the Large Language Models (LLMs) in response to certain prompts. We propose integrating risk-…
Pedagogical Alignment of Large Language Models
Shashank Sonkar, Kangqi Ni, Sapana Chaudhary +1
Large Language Models (LLMs), when used in educational settings without pedagogical fine-tuning, often provide immediate answers rather than guiding students through the problem-so…
Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems
Ting-Jui Chang, Sapana Chaudhary, Dileep Kalathil +1
This paper addresses safe distributed online optimization over an unknown set of linear safety constraints. A network of agents aims at jointly minimizing a global, time-varying fu…
Enhanced Meta Reinforcement Learning using Demonstrations in Sparse Reward Environments
Desik Rengarajan, Sapana Chaudhary, Jaewon Kim +2
Meta reinforcement learning (Meta-RL) is an approach wherein the experience gained from solving a variety of tasks is distilled into a meta-policy. The meta-policy, when adapted ov…
Safe Online Convex Optimization with Unknown Linear Safety Constraints
Sapana Chaudhary, Dileep Kalathil
We study the problem of safe online convex optimization, where the action at each time step must satisfy a set of linear safety constraints. The goal is to select a sequence of act…
Smooth Imitation Learning via Smooth Costs and Smooth Policies
Sapana Chaudhary, Balaraman Ravindran
Imitation learning (IL) is a popular approach in the continuous control setting as among other reasons it circumvents the problems of reward mis-specification and exploration in re…