16 citations · 25 across the 7 of their papers we have counts for
7 papers
SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades
Man Ho Lam, Chaozheng Wang, Hange Liu +5
Coding agents powered by large language models are increasingly expected to perform realistic software maintenance tasks beyond isolated issue resolution. Existing benchmarks have…
Reranking Laws for Language Generation: A Communication-Theoretic Perspective
António Farinhas, Haau-Sing Li, André F. T. Martins
To ensure large language models (LLMs) are used safely, one must reduce their propensity to hallucinate or to generate unacceptable answers. A simple and often used strategy is to…
DOCE: Finding the Sweet Spot for Execution-Based Code Generation
Haau-Sing Li, Patrick Fernandes, Iryna Gurevych +1
Recently, a diverse set of decoding and reranking procedures have been shown effective for LLM-based code generation. However, a comprehensive framework that links and experimental…
Uncertainty in Natural Language Generation: From Theory to Applications
Joris Baan, Nico Daheim, Evgenia Ilia +7
Recent advances of powerful Language Models have allowed Natural Language Generation (NLG) to emerge as an important technology that can not only perform traditional tasks like sum…
Python Code Generation by Asking Clarification Questions
Haau-Sing Li, Mohsen Mesgar, André F. T. Martins +1
Code generation from text requires understanding the user's intent from a natural language description and generating an executable code snippet that satisfies this intent. While r…
When Do You Need Billions of Words of Pretraining Data?
Yian Zhang, Alex Warstadt, Haau-Sing Li +1
NLP is currently dominated by general-purpose pretrained language models like RoBERTa, which achieve strong performance on NLU tasks through pretraining on billions of words. But w…
Learning Which Features Matter: RoBERTa Acquires a Preference for Linguistic Generalizations (Eventually)
Alex Warstadt, Yian Zhang, Haau-Sing Li +2
One reason pretraining on self-supervised linguistic tasks is effective is that it teaches models features that are helpful for language understanding. However, we want pretrained…