64 citations · 439 across the 25 of their papers we have counts for
27 papers
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning
Junru Chen, Yang Yang, Tao Yu +3
Epilepsy is one of the most serious neurological diseases, affecting 1-2% of the world's population. The diagnosis of epilepsy depends heavily on the recognition of epileptic waves…
One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Hongjin Su, Weijia Shi, Jungo Kasai +7
We introduce INSTRUCTOR, a new method for computing text embeddings given task instructions: every text input is embedded together with instructions explaining the use case (e.g.,…
Coder Reviewer Reranking for Code Generation
Tianyi Zhang, Tao Yu, Tatsunori B. Hashimoto +4
Sampling diverse programs from a code language model and reranking with model likelihood is a popular method for code generation but it is prone to preferring degenerate solutions.…
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation
Yuhang Lai, Chengxi Li, Yiming Wang +7
We introduce DS-1000, a code generation benchmark with a thousand data science problems spanning seven Python libraries, such as NumPy and Pandas. Compared to prior works, DS-1000…
Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play
Qi Liu, Zihuiwen Ye, Tao Yu +2
The task of context-dependent text-to-SQL aims to convert multi-turn user utterances to formal SQL queries. This is a challenging task due to both the scarcity of training data fro…
NL2INTERFACE: Interactive Visualization Interface Generation from Natural Language Queries
Yiru Chen, Ryan Li, Austin Mac +3
We develop NL2INTERFACE to explore the potential of generating usable interactive multi-visualization interfaces from natural language queries. With NL2INTERFACE, users can directl…
Selective Annotation Makes Language Models Better Few-Shot Learners
Hongjin Su, Jungo Kasai, Chen Henry Wu +8
Many recent approaches to natural language tasks are built on the remarkable abilities of large language models. Large language models can perform in-context learning, where they l…
N-Grammer: Augmenting Transformers with latent n-grams
Aurko Roy, Rohan Anil, Guangda Lai +13
Transformer models have recently emerged as one of the foundational models in natural language processing, and as a byproduct, there is significant recent interest and investment i…
Random Laplacian Features for Learning with Hyperbolic Space
Tao Yu, Christopher De Sa
Due to its geometric properties, hyperbolic space can support high-fidelity embeddings of tree- and graph-structured data, upon which various hyperbolic networks have been develope…
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
Tianbao Xie, Chen Henry Wu, Peng Shi +20
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases and question answering over knowledge bases.…
DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization
Ziming Mao, Chen Henry Wu, Ansong Ni +7
Transformer-based models have achieved state-of-the-art performance on short-input summarization. However, they still struggle with summarizing longer text. In this paper, we prese…
Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions
Naihao Deng, Shuaichen Chang, Peng Shi +2
Existing text-to-SQL research only considers complete questions as the input, but lay-users might strive to formulate a complete question. To build a smarter natural language inter…
An Exploratory Study on Long Dialogue Summarization: What Works and What's Next
Yusen Zhang, Ansong Ni, Tao Yu +6
Dialogue summarization helps readers capture salient information from long conversations in meetings, interviews, and TV series. However, real-world dialogues pose a great challeng…
SummerTime: Text Summarization Toolkit for Non-experts
Ansong Ni, Zhangir Azerbayev, Mutethia Mutuma +5
Recent advances in summarization provide models that can generate summaries of higher quality. Such models now exist for a number of summarization tasks, including query-based summ…
Logic-Consistency Text Generation from Semantic Parses
Chang Shu, Yusen Zhang, Xiangyu Dong +3
Text generation from semantic parses is to generate textual descriptions for formal representation inputs such as logic forms and SQL queries. This is challenging due to two reason…
QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
Ming Zhong, Da Yin, Tao Yu +8
Meetings are a key component of human collaboration. As increasing numbers of meetings are recorded and transcribed, meeting summaries have become essential to remind those who may…
Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text-to-SQL
Yusen Zhang, Xiangyu Dong, Shuaichen Chang +3
Neural models have achieved significant results on the text-to-SQL task, in which most current work assumes all the input questions are legal and generates a SQL query for any inpu…
Semantic Evaluation for Text-to-SQL with Distilled Test Suites
Ruiqi Zhong, Tao Yu, Dan Klein
We propose test suite accuracy to approximate semantic accuracy for Text-to-SQL models. Our method distills a small test suite of databases that achieves high code coverage for the…
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Tao Yu, Chien-Sheng Wu, Xi Victoria Lin +6
We present GraPPa, an effective pre-training approach for table semantic parsing that learns a compositional inductive bias in the joint representations of textual and tabular data…
DART: Open-Domain Structured Data Record to Text Generation
Linyong Nan, Dragomir Radev, Rui Zhang +21
We present DART, an open domain structured DAta Record to Text generation dataset with over 82k instances (DARTs). Data-to-Text annotations can be a costly process, especially when…
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases
Tao Yu, Rui Zhang, He Yang Er +21
We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained f…
Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions
Rui Zhang, Tao Yu, He Yang Er +7
We focus on the cross-domain context-dependent text-to-SQL generation task. Based on the observation that adjacent natural language questions are often linguistically dependent and…
SParC: Cross-Domain Semantic Parsing in Context
Tao Yu, Rui Zhang, Michihiro Yasunaga +16
We present SParC, a dataset for cross-domainSemanticParsing inContext that consists of 4,298 coherent question sequences (12k+ individual questions annotated with SQL queries). It…
SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task
Tao Yu, Michihiro Yasunaga, Kai Yang +4
Most existing studies in text-to-SQL tasks do not require generating complex SQL queries with multiple clauses or sub-queries, and generalizing to new, unseen databases. In this pa…