68 citations · 228 across the 46 of their papers we have counts for
4 papers · 1 filter
Knowing When Thinking Is Not Enough: Teaching Small Reasoning Models to Reason Beyond Their Parametric Knowledge
Chanuk Lee, Minki Kang, Sangwoo Park +3
Scaling test-time computation is a powerful way to improve language-model reasoning, and is particularly appealing for small reasoning models (sRMs) that are cheap to serve. Howeve…
PREPING: Zero-Task Agent Memory Construction via Self-Practice
Yumin Choi, Sangwoo Park, Minki Kang +2
Agent memory is typically constructed either offline from curated demonstrations or online from post-deployment interactions. However, regardless of how it is built, an agent faces…
Rethinking Reward Models for Multi-Domain Test-Time Scaling
Dong Bok Lee, Seanie Lee, Sangwoo Park +12
The reliability of large language models (LLMs) during test-time scaling is often assessed with \emph{external verifiers} or \emph{reward models} that distinguish correct reasoning…
Exploring The Spatial Reasoning Ability of Neural Models in Human IQ Tests
Hyunjae Kim, Yookyung Koh, Jinheon Baek +1
Although neural models have performed impressively well on various tasks such as image recognition and question answering, their reasoning ability has been measured in only few stu…