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Lin Tan

9 accepted papers

2025

Can Language Models Replace Programmers for Coding? REPOCOD Says ‘Not Yet’

ACL 2025long

Recently, a number of repository-level code generation benchmarks–such as CoderEval, DevEval, RepoEval, RepoBench, and LongCode-Arena–have emerged to evaluate the capabilities of large language models (LLMs) beyond standalone benchmarks like HumanEval and MBPP. Thus, a natural question is, would LLM…

2025

CoRe: Benchmarking LLMs’ Code Reasoning Capabilities through Static Analysis Tasks

NeurIPS 2025spotlight

Large language models (LLMs) have been widely adopted across diverse domains of software engineering, such as code generation, program repair, and vulnerability detection. These applications require understanding beyond surface-level code patterns: value propagation, control flow, and interdependenc…

Cited by 0SourceScholar
2025

LATTE: Improving Latex Recognition for Tables and Formulae with Iterative Refinement

AAAI 2025technical

Portable Document Format (PDF) files are dominantly used for storing and disseminating scientific research, legal documents, and tax information. LaTeX is a popular application for creating PDF documents. Despite its advantages, LaTeX is not WYSWYG---what you see is what you get, i.e., the LaTeX sou…

2025

Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning

ICLR 2025poster

Binary code analysis is the foundation of crucial tasks in the security domain; thus building effective binary analysis techniques is more important than ever. Large language models (LLMs) although have brought impressive improvement to source code tasks, do not directly generalize to assembly code…

Cited by 0SourcePDFScholar
2025

SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models

ICRA 2025

Despite significant advancements in large language models (LLMs) that enhance robot agents' understanding and execution of natural language (NL) commands, ensuring the agents adhere to user-specified constraints remains challenging, particularly for complex commands and long-horizon tasks. To addres

Cited by 20SourcecodeScholar
2025

WAFFLE: Fine-tuning Multi-Modal Model for Automated Front-End Development

ACL 2025long

Web development involves turning UI designs into functional webpages, which can be difficult for both beginners and experienced developers due to the complexity of HTML’s hierarchical structures and styles. While Large Language Models (LLMs) have shown promise in generating source code, two major ch…

2024

SDRNet: Saliency-Guided Dynamic Restoration Network for Rain and Haze Removal in Nighttime Images

ICASSP 2024accepted

Due to the different physical imaging models, most haze or rain removal methods for daytime images are not suitable for nighttime images. Fog effect produced by the accumulation of rain also brings great challenges to the restoration of low-light nighttime images. To deal well with the multiple nois…

Cited by 0SourceScholar
2023

DisGUIDE: Disagreement-Guided Data-Free Model Extraction

AAAI 2023technical

Recent model-extraction attacks on Machine Learning as a Service (MLaaS) systems have moved towards data-free approaches, showing the feasibility of stealing models trained with difficult-to-access data. However, these attacks are ineffective or limited due to the low accuracy of extracted models an…

2021

Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training

NeurIPS 2021poster

Deep learning (DL) systems have been gaining popularity in critical tasks such as credit evaluation and crime prediction. Such systems demand fairness. Recent work shows that DL software implementations introduce variance: identical DL training runs (i.e., identical network, data, configuration, sof…

Cited by 61SourcePDFScholar