activity
20212025
most citedBinary Classifier Optimization for Large Language Model Alignment

3 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2025★ 2 cited

Kanana: Compute-efficient Bilingual Language Models

Kanana LLM Team, Yunju Bak, Hojin Lee +26

We introduce Kanana, a series of bilingual language models that demonstrate exceeding performance in Korean and competitive performance in English. The computational cost of Kanana…

cs.CL2024

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…

cs.LG2024★ 3 cited

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…

cs.CL2023

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…

cs.CL2023★ 1 cited

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…

cs.LG2022★ 2 cited

LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward

Daejin Jo, Sungwoong Kim, Daniel Wontae Nam +4

Episodic count has been widely used to design a simple yet effective intrinsic motivation for reinforcement learning with a sparse reward. However, the use of episodic count in a h…

cs.LG2021

GMAC: A Distributional Perspective on Actor-Critic Framework

Daniel Wontae Nam, Younghoon Kim, Chan Y. Park

In this paper, we devise a distributional framework on actor-critic as a solution to distributional instability, action type restriction, and conflation between samples and statist…