4 citations · 10 across the 17 of their papers we have counts for
6 papers · 1 filter
Who's Behind the Text? Robust Model Authorship Attribution
Minseok Ko, Hyunseok Lee, Woomin Song +3
As large language models (LLMs) are increasingly used to generate text, their misuse has become a growing societal problem, with implications for academic misconduct, model distill…
IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents
Daewon Choi, Kyunghyun Park, Woomin Song +4
Large language model (LLM)-based agents solve complex tasks by leveraging multi-step reasoning with iterative tool calls and environment interactions, which incur idle time while w…
ExComm: Exploration-Stage Communication for Error-Resilient Agentic Test-Time Scaling
Woomin Song, Beomjun Kim, Daewon Choi +4
A common failure mode in long-horizon agentic test-time scaling is error propagation, where factual errors or invalid deductions introduced at intermediate steps persist in the age…
Scalable and Robust LLM Unlearning by Correcting Responses with Retrieved Exclusions
Junbeom Kim, Kyuyoung Kim, Jihoon Tack +2
Language models trained on web-scale corpora risk memorizing and exposing sensitive information, prompting the need for effective machine unlearning. Prior methods mainly focus on…
DS-STAR: Data Science Agent for Solving Diverse Tasks across Heterogeneous Formats and Open-Ended Queries
Jaehyun Nam, Jinsung Yoon, Jiefeng Chen +3
While large language models (LLMs) have shown promise in automating data science, existing agents often struggle with the complexity of real-world workflows that require exploring…
Think Clearly: Improving Reasoning via Redundant Token Pruning
Daewon Choi, Jimin Lee, Jihoon Tack +7
Recent large language models have shown promising capabilities in long-form reasoning, following structured chains of thought before arriving at a final answer. However, we observe…