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20192023
most citedL2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models

3 citations · 4 across the 5 of their papers we have counts for

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cs.CL20233 cited

L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models

Ansong Ni, Pengcheng Yin, Yilun Zhao +11

Recently, large language models (LLMs), especially those that are pretrained on code, have demonstrated strong capabilities in generating programs from natural language inputs in a…

cs.CL2021

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…

cs.CL2021

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…

cs.CL2021

Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization

Ansong Ni, Matt Gardner, Pradeep Dasigi

Question Answering (QA) tasks requiring information from multiple documents often rely on a retrieval model to identify relevant information for reasoning. The retrieval model is t…

cs.CL20191 cited

Merging Weak and Active Supervision for Semantic Parsing

Ansong Ni, Pengcheng Yin, Graham Neubig

A semantic parser maps natural language commands (NLs) from the users to executable meaning representations (MRs), which are later executed in certain environment to obtain user-de…