Papers by Dongkyu Choi
Local Temperature Beam Search: Avoid Neural Text DeGeneration via Enhanced Calibration (2023.findings-acl)
Copied to clipboard
Dongkyu Lee, Gyeonghun Kim, Janghoon Han, Taesuk Hong, Yi-Reun Kim, Stanley Jungkyu Choi, Nevin L. Zhang
| Challenge: | Existing approaches to inference have been based on stochastic decoding but they sacrifice output quality due to randomness. |
| Approach: | They propose a deterministic decoding scheme, local temperature beam search, which reduces repetition while maintaining the level of coherence as in beam search. |
| Outcome: | The proposed inference scheme reduces repetition while maintaining coherence as in beam search. |
LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods for knowledge editing in Large Language Models face difficulties with multi-hop questions that require accurate fact identification and sequential logical reasoning. |
| Approach: | They propose a method that merges explicit knowledge representations of Knowledge Graphs with the linguistic flexibility of Large Language Models to convert free-form language into structured queries and fact triples. |
| Outcome: | The proposed method significantly surpasses state-of-the-art knowledge editing methods in the multi-hop question answering benchmark, MQuAKE. |
From Grounding to Manipulation: Case Studies of Foundation Model Integration in Embodied Robotic Systems (2025.findings-emnlp)
Copied to clipboard
| Challenge: | a new study examines the operational characteristics of different integration strategies for robotics . end-to-end vision-language-action models implicitly unify perception and planning . |
| Approach: | They propose end-to-end vision-language-action models that implicitly unify perception and planning . they also propose modular pipelines using either vision-linguistic models or MLLMs . |
| Outcome: | The proposed frameworks implicitly unify perception and planning, and modular pipelines using either vision-language models or multimodal large language models. |