9 citations · 15 across the 5 of their papers we have counts for
7 papers · 1 filter
ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Siddhant Waghjale, Vishruth Veerendranath, Zora Zhiruo Wang +1
Although large language models (LLMs) have been largely successful in generating functionally correct programs, conditioning models to produce efficient solutions while ensuring co…
What Are Tools Anyway? A Survey from the Language Model Perspective
Zhiruo Wang, Zhoujun Cheng, Hao Zhu +2
Language models (LMs) are powerful yet mostly for text generation tasks. Tools have substantially enhanced their performance for tasks that require complex skills. However, many wo…
Learning to Filter Context for Retrieval-Augmented Generation
Zhiruo Wang, Jun Araki, Zhengbao Jiang +2
On-the-fly retrieval of relevant knowledge has proven an essential element of reliable systems for tasks such as open-domain question answering and fact verification. However, beca…
API-Assisted Code Generation for Question Answering on Varied Table Structures
Yihan Cao, Shuyi Chen, Ryan Liu +2
A persistent challenge to table question answering (TableQA) by generating executable programs has been adapting to varied table structures, typically requiring domain-specific log…
Improving Factuality of Abstractive Summarization via Contrastive Reward Learning
I-Chun Chern, Zhiruo Wang, Sanjan Das +3
Modern abstractive summarization models often generate summaries that contain hallucinated or contradictory information. In this paper, we propose a simple but effective contrastiv…
Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer
Zhengbao Jiang, Luyu Gao, Jun Araki +4
Systems for knowledge-intensive tasks such as open-domain question answering (QA) usually consist of two stages: efficient retrieval of relevant documents from a large corpus and d…