3 papers
cs.LG2026
FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation
Dong Liu, Yanxuan Yu, Jiayi Zhang +3
Diffusion Transformers (DiT) are powerful generative models but remain computationally intensive due to their iterative structure and deep transformer stacks. To alleviate this ine…
cs.CL2026
KDCM: Reducing Hallucination in LLMs through Explicit Reasoning Structures
Jinbo Hao, Kai Yang, Qingzhen Su +2
To mitigate hallucinations in large language models (LLMs), we propose a framework that focuses on errors induced by prompts. Our method extends a chain-style knowledge distillatio…
cs.CL2026
Mitigating Prompt-Induced Hallucinations in Large Language Models via Structured Reasoning
Jinbo Hao, Kai Yang, Qingzhen Su +3
To address hallucination issues in large language models (LLMs), this paper proposes a method for mitigating prompt-induced hallucinations. Building on a knowledge distillation cha…