4 citations · 11 across the 6 of their papers we have counts for
6 papers
TLCR: Token-Level Continuous Reward for Fine-grained Reinforcement Learning from Human Feedback
Eunseop Yoon, Hee Suk Yoon, SooHwan Eom +7
Reinforcement Learning from Human Feedback (RLHF) leverages human preference data to train language models to align more closely with human essence. These human preference data, ho…
Binary Classifier Optimization for Large Language Model Alignment
Seungjae Jung, Gunsoo Han, Daniel Wontae Nam +1
In real-world services such as ChatGPT, aligning models based on user feedback is crucial for improving model performance. However, due to the simplicity and convenience of providi…
Hexa: Self-Improving for Knowledge-Grounded Dialogue System
Daejin Jo, Daniel Wontae Nam, Gunsoo Han +4
A common practice in knowledge-grounded dialogue generation is to explicitly utilize intermediate steps (e.g., web-search, memory retrieval) with modular approaches. However, data…
Effortless Integration of Memory Management into Open-Domain Conversation Systems
Eunbi Choi, Kyoung-Woon On, Gunsoo Han +6
Open-domain conversation systems integrate multiple conversation skills into a single system through a modular approach. One of the limitations of the system, however, is the absen…
Boundary-aware Self-supervised Learning for Video Scene Segmentation
Jonghwan Mun, Minchul Shin, Gunsoo Han +4
Self-supervised learning has drawn attention through its effectiveness in learning in-domain representations with no ground-truth annotations; in particular, it is shown that prope…
Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts
Minchul Shin, Jonghwan Mun, Kyoung-Woon On +3
The VALUE (Video-And-Language Understanding Evaluation) benchmark is newly introduced to evaluate and analyze multi-modal representation learning algorithms on three video-and-lang…