1.5k citations · 3.5k across the 68 of their papers we have counts for
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ReCode: Robustness Evaluation of Code Generation Models
Shiqi Wang, Zheng Li, Haifeng Qian +11
Code generation models have achieved impressive performance. However, they tend to be brittle as slight edits to a prompt could lead to very different generations; these robustness…
Importance of Synthesizing High-quality Data for Text-to-SQL Parsing
Yiyun Zhao, Jiarong Jiang, Yiqun Hu +14
Recently, there has been increasing interest in synthesizing data to improve downstream text-to-SQL tasks. In this paper, we first examined the existing synthesized datasets and di…
CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad +5
While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file c…
Multi-lingual Evaluation of Code Generation Models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang +22
We present new benchmarks on evaluation code generation models: MBXP and Multilingual HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are generated…
ContraCLM: Contrastive Learning For Causal Language Model
Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad +9
Despite exciting progress in causal language models, the expressiveness of the representations is largely limited due to poor discrimination ability. To remedy this issue, we prese…
DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases
Donghan Yu, Sheng Zhang, Patrick Ng +7
Question answering over knowledge bases (KBs) aims to answer natural language questions with factual information such as entities and relations in KBs. Previous methods either gene…
Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding
Jun Wang, Patrick Ng, Alexander Hanbo Li +5
Most recent research on Text-to-SQL semantic parsing relies on either parser itself or simple heuristic based approach to understand natural language query (NLQ). When synthesizing…
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction
Sheng Zhang, Patrick Ng, Zhiguo Wang +1
Relation extraction is an important but challenging task that aims to extract all hidden relational facts from the text. With the development of deep language models, relation extr…
Learning Dialogue Representations from Consecutive Utterances
Zhihan Zhou, Dejiao Zhang, Wei Xiao +4
Learning high-quality dialogue representations is essential for solving a variety of dialogue-oriented tasks, especially considering that dialogue systems often suffer from data sc…
DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization
Zheng Li, Zijian Wang, Ming Tan +5
Large-scale pre-trained sequence-to-sequence models like BART and T5 achieve state-of-the-art performance on many generative NLP tasks. However, such models pose a great challenge…