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Yuxiang Lin

3 accepted papers

2026

Do LLM Agents Know How to Ground, Recover, and Assess? Evaluating Epistemic Competence in Information-Seeking Agents

ICLR 2026poster

Recent work has explored training Large Language Model (LLM) search agents with reinforcement learning (RL) for open-domain question answering. However, most evaluations focus solely on final answer accuracy, overlooking how these agents reason with and act on external evidence. We introduce **SeekB…

Cited by 0SourcecodeScholar
2026

HyperST: Hierarchical Hyperbolic Learning for Spatial Transcriptomics Prediction

CVPR 2026

Spatial Transcriptomics (ST) merges the benefits of pathology images and gene expression, linking molecular profiles with tissue structure to analyze spot-level function comprehensively. Predicting gene expression from histology images is a cost-effective alternative to expensive ST technologies. Ho

Cited by 0SourcecodeScholar
2024

Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning

NeurIPS 2024poster

Accurate emotion perception is crucial for various applications, including human-computer interaction, education, and counseling. However, traditional single-modality approaches often fail to capture the complexity of real-world emotional expressions, which are inherently multimodal. Moreover, exist…