5 citations · 6 across the 5 of their papers we have counts for
6 papers
Towards Efficient Reasoning: Learning Causal Shortcuts for Diffusion Language Models
Dian Jin, Kairong Han, Baohong Li +5
Diffusion Language Models (DLMs) have attracted significant attention for their strong reasoning ability. However, under a bidirectional attention mechanism, DLMs operate over an e…
CDLM: Causal Concept-Guided Diffusion Large Language Models
Kairong Han, Nuanqiao Shan, Ziyu Zhao +6
Autoregressive (AR) language models and Diffusion Language Models (DLMs) constitute the two principal paradigms of large language models. However, both paradigms suffer from insuff…
Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method
Kairong Han, Weidong Huang, Taiyang Zhou +2
In the online ride-hailing pricing context, companies often conduct randomized controlled trials (RCTs) and utilize uplift models to assess the effect of discounts on customer orde…
CAT: Causal Attention Tuning For Injecting Fine-grained Causal Knowledge into Large Language Models
Kairong Han, Wenshuo Zhao, Ziyu Zhao +3
Large Language Models (LLMs) have achieved remarkable success across various domains. However, a fundamental question remains: Can LLMs effectively utilize causal knowledge for pre…
Causality for Large Language Models
Anpeng Wu, Kun Kuang, Minqin Zhu +7
Recent breakthroughs in artificial intelligence have driven a paradigm shift, where large language models (LLMs) with billions or trillions of parameters are trained on vast datase…
Causal Agent based on Large Language Model
Kairong Han, Kun Kuang, Ziyu Zhao +2
The large language model (LLM) has achieved significant success across various domains. However, the inherent complexity of causal problems and causal theory poses challenges in ac…