24 citations · 52 across the 27 of their papers we have counts for
8 papers · 1 filter
Can LLMs Imagine Moral Alternatives Beyond Binary Dilemmas?
Jongchan Choi, Nari Yang, Sung Soo Park +4
As LLMs increasingly serve as moral advisors and agents, they must address conflicts between competing values. Yet prior work on moral dilemmas overlooks a central aspect of human…
Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems
Zaid Khan, Elias Stengel-Eskin, Archiki Prasad +2
Scientists often infer abstract procedures from specific instances of problems and use the abstractions to generate new, related instances. For example, programs encoding the forma…
DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
Zaid Khan, Elias Stengel-Eskin, Jaemin Cho +1
The process of creating training data to teach models is currently driven by humans, who manually analyze model weaknesses and plan how to create data that improves a student model…
EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents
Abhay Zala, Jaemin Cho, Han Lin +2
Recent SOTA approaches for embodied learning via interaction directly employ large language models (LLMs) as agents to determine the next steps in an environment. Due to their worl…
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer
Zineng Tang, Jaemin Cho, Hao Tan +1
Since visual perception can give rich information beyond text descriptions for world understanding, there has been increasing interest in leveraging visual grounding for language l…
Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan +1
Existing methods for vision-and-language learning typically require designing task-specific architectures and objectives for each task. For example, a multi-label answer classifier…