5 papers
Concept Component Analysis: A Principled Approach for Concept Extraction in LLMs
Yuhang Liu, Erdun Gao, Dong Gong +2
Developing human understandable interpretation of large language models (LLMs) becomes increasingly critical for their deployment in essential domains. Mechanistic interpretability…
Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning
Tianjiao Jiang, Zhen Zhang, Yuhang Liu +1
Few-shot learning (FSL) often requires effective adaptation of models using limited labeled data. However, most existing FSL methods rely on entangled representations, requiring th…
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
Yichao Cai, Yuhang Liu, Erdun Gao +4
Multimodal representation learning, exemplified by multimodal contrastive learning (MMCL) using image-text pairs, aims to learn powerful representations by aligning cues across mod…
Analytic DAG Constraints for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong +6
Recovering the underlying Directed Acyclic Graph (DAG) structures from observational data presents a formidable challenge, partly due to the combinatorial nature of the DAG-constra…
InvariantStock: Learning Invariant Features for Mastering the Shifting Market
Haiyao Cao, Jinan Zou, Yuhang Liu +4
Accurately predicting stock returns is crucial for effective portfolio management. However, existing methods often overlook a fundamental issue in the market, namely, distribution…