activity
20232026
most citedDiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models

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

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.AI2026

Arena-T2I Hard: Benchmarking and Improving Faithfulness with Dependency-Aware Checklist

Yuanhao Ban, Tong Xie, Sohyun An +6

Faithfulness -- how precisely a generated image aligns with its prompt -- is increasingly central to the real-world utility of text-to-image (T2I) models. Existing faithfulness ben…

cs.LG2026

A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

Tong Xie, Yuanhao Ban, Yunqi Hong +3

Supervised fine-tuning (SFT) typically maximizes the likelihood of every token in a demonstrated trajectory. However, an observed token can be non-unique, noisy, or misaligned with…

cs.IR2026

FRESCO: Benchmarking and Optimizing Re-rankers for Evolving Semantic Conflict in Retrieval-Augmented Generation

Sohyun An, Hayeon Lee, Shuibenyang Yuan +4

Retrieval-Augmented Generation (RAG) is a key approach to mitigating the temporal staleness of large language models (LLMs) by grounding responses in up-to-date evidence. Within th…

cs.AI2026

Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training

Sohyun An, Shuibenyang Yuan, Hayeon Lee +2

Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches predominantly rely on gold…

cs.CR2026

T-MAP: Red-Teaming LLM Agents with Trajectory-aware Evolutionary Search

Hyomin Lee, Sangwoo Park, Yumin Choi +3

While prior red-teaming efforts have focused on eliciting harmful text outputs from large language models (LLMs), such approaches fail to capture agent-specific vulnerabilities tha…