4 citations · 6 across the 5 of their papers we have counts for
6 papers
Collective Bias Mitigation via Model Routing and Collaboration
Mingzhe Du, Luu Anh Tuan, Xiaobao Wu +7
Large language models (LLMs) are increasingly deployed in public health, finance, and governance, requiring both accuracy and societal value alignment. Despite recent advances, LLM…
-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Zhenbang Du, Kejing Xia, Xinrui Zhong +6
Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction. However, practical dLLM decoding…
BlockBatch: Multi-Scale Consensus Decoding for Efficient Diffusion Language Model Inference
Xiaoyou Wu, Cheng-Jhih Shih, Binfei Ji +2
Diffusion language models (dLLMs) generate text by iteratively denoising multiple token positions in parallel, offering an attractive alternative to strictly autoregressive decodin…
CodeArena: A Collective Evaluation Platform for LLM Code Generation
Mingzhe Du, Anh Tuan Luu, Bin Ji +5
Large Language Models (LLMs) have reshaped code generation by synergizing their exceptional comprehension of natural language and programming syntax, thereby substantially boosting…
Mercury: A Code Efficiency Benchmark for Code Large Language Models
Mingzhe Du, Anh Tuan Luu, Bin Ji +2
Amidst the recent strides in evaluating Large Language Models for Code (Code LLMs), existing benchmarks have mainly focused on the functional correctness of generated code, neglect…
From Static to Dynamic: A Continual Learning Framework for Large Language Models
Mingzhe Du, Anh Tuan Luu, Bin Ji +1
The vast number of parameters in large language models (LLMs) endows them with remarkable capabilities, allowing them to excel in a variety of natural language processing tasks. Ho…