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David Lo

3 accepted papers

2026

Autoregressive, Yet Revisable: In Decoding Revision for Secure Code Generation

ICML 2026poster

Large Language Model (LLM) based code generation is predominantly formulated as a strictly monotonic process, appending tokens linearly to an immutable prefix. This formulation contrasts to the cognitive process of programming, which is inherently interleaved with forward generation and on-the-fly r…

Cited by 0SourceScholar
2025

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

ICLR 2025oral

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks range from software engineering development to general-purpose reasoning. While current benchmarks have shown that LLMs can solve tasks using programs like human develop…

Cited by 609SourcePDFScholar
2025

TACLR: A Scalable and Efficient Retrieval-based Method for Industrial Product Attribute Value Identification

ACL 2025long

Product Attribute Value Identification (PAVI) involves identifying attribute values from product profiles, a key task for improving product search, recommendation, and business analytics on e-commerce platforms.However, existing PAVI methods face critical challenges, such as inferring implicit value…