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Shenghao Liu

4 accepted papers

2026

BEST: Benchmarking Efficiency in Space and Time for LLM-Generated Code

ICML 2026poster

Large language models (LLMs) have revolutionized research in software engineering, and among various tasks, LLM-based code synthesis is promising. A recent line of benchmarks aims to evaluate LLM-generated codes in time efficiency, beyond their correctness. However, *space*, another vital aspect of …

Cited by 0SourceScholar
2025

DiMa: Understanding the Hardness of Online Matching Problems via Diffusion Models

ICML 2025poster

We explore the potential of \emph{AI-enhanced combinatorial optimization theory}, taking online bipartite matching (OBM) as a case study. In the theoretical study of OBM, the \emph{hardness} corresponds to a performance \emph{upper bound} of a specific online algorithm or any possible online algorit…

Cited by 0SourcePDFScholar
2025

Understanding the Unfairness in Network Quantization

ICML 2025poster

Network quantization, one of the most widely studied model compression methods, effectively quantizes a floating-point model to obtain a fixed-point one with negligible accuracy loss. Although great success was achieved in reducing the model size, it may exacerbate the unfairness in model accuracy…

Cited by 0SourcePDFScholar
2024

DCSANet: Dual Cross-channel and Spatial Attention Make RGB-T Object Detection Better

IROS 2024poster

Multimodal image pairs can make object detection more reliable in challenging environments, so RGB-T object detection has gained extensive attention over the past decade. To alleviate the complementarity of the visible and thermal modality, we propose a novel lightweight Feature Enhancement-fusion M…

Cited by 0SourceScholar