5 citations · 13 across the 11 of their papers we have counts for
11 papers
Towards Direct Evaluation of Harness Optimizers via Priority Ranking
Kai Tzu-iunn Ong, Minseok Kang, Dongwook Choi +11
Harness optimization enables automated agent creation by having an optimizer agent iteratively update the harness of target agents. Despite its success, current studies evaluate op…
PAC-BENCH: Evaluating Multi-Agent Collaboration under Privacy Constraints
Minjun Park, Donghyun Kim, Hyeonjong Ju +5
We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. However, the dynamics of mult…
EXAONE 4.5 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +55
This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…
Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifiers
Wooseok Seo, Seungju Han, Jaehun Jung +6
Fact verification is essential for ensuring the reliability of LLM applications. In this study, we evaluate 12 pre-trained LLMs and one specialized fact-verifier, including frontie…
Persona Dynamics: Unveiling the Impact of Personality Traits on Agents in Text-Based Games
Seungwon Lim, Seungbeen Lee, Dongjun Min +1
Artificial agents are increasingly central to complex interactions and decision-making tasks, yet aligning their behaviors with desired human values remains an open challenge. In t…
When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research
Guijin Son, Jiwoo Hong, Honglu Fan +8
Recent advances in large language models (LLMs) have fueled the vision of automated scientific discovery, often called AI Co-Scientists. To date, prior work casts these systems as…
VisEscape: A Benchmark for Evaluating Exploration-driven Decision-making in Virtual Escape Rooms
Seungwon Lim, Sungwoong Kim, Jihwan Yu +3
Escape rooms present a unique cognitive challenge that demands exploration-driven planning: with the sole instruction to 'escape the room', players must actively search their envir…
MASS: Overcoming Language Bias in Image-Text Matching
Jiwan Chung, Seungwon Lim, Sangkyu Lee +1
Pretrained visual-language models have made significant advancements in multimodal tasks, including image-text retrieval. However, a major challenge in image-text matching lies in…
Can visual language models resolve textual ambiguity with visual cues? Let visual puns tell you!
Jiwan Chung, Seungwon Lim, Jaehyun Jeon +2
Humans possess multimodal literacy, allowing them to actively integrate information from various modalities to form reasoning. Faced with challenges like lexical ambiguity in text,…
Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics
Seungbeen Lee, Seungwon Lim, Seungju Han +9
Recent advancements in Large Language Models (LLMs) have led to their adaptation in various domains as conversational agents. We wonder: can personality tests be applied to these a…
CLARA: Classifying and Disambiguating User Commands for Reliable Interactive Robotic Agents
Jeongeun Park, Seungwon Lim, Joonhyung Lee +4
In this paper, we focus on inferring whether the given user command is clear, ambiguous, or infeasible in the context of interactive robotic agents utilizing large language models…