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20212025
most citedSWE-bench: Can Language Models Resolve Real-World GitHub Issues?

53 citations · 187 across the 29 of their papers we have counts for

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Showing 2023 · cs.CLShow all

9 papers · 2 filters

cs.CL2023★ 6 cited

FireAct: Toward Language Agent Fine-tuning

Baian Chen, Chang Shu, Ehsan Shareghi +3

Recent efforts have augmented language models (LMs) with external tools or environments, leading to the development of language agents that can reason and act. However, most of the…

cs.CL2023★ 53 cited

SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Carlos E. Jimenez, John Yang, Alexander Wettig +4

Language models have outpaced our ability to evaluate them effectively, but for their future development it is essential to study the frontier of their capabilities. We find real-w…

cs.CL2023★ 1 cited

COLLIE: Systematic Construction of Constrained Text Generation Tasks

Shunyu Yao, Howard Chen, Austin W. Hanjie +2

Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models. Howeve…

cs.CL2023★ 1 cited

InstructEval: Systematic Evaluation of Instruction Selection Methods

Anirudh Ajith, Chris Pan, Mengzhou Xia +2

In-context learning (ICL) performs tasks by prompting a large language model (LLM) using an instruction and a small set of annotated examples called demonstrations. Recent work has…

cs.CL2023★ 8 cited

InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback

John Yang, Akshara Prabhakar, Karthik Narasimhan +1

Humans write code in a fundamentally interactive manner and rely on constant execution feedback to correct errors, resolve ambiguities, and decompose tasks. While LLMs have recentl…

cs.CL2023

Referral Augmentation for Zero-Shot Information Retrieval

Michael Tang, Shunyu Yao, John Yang +1

We propose Referral-Augmented Retrieval (RAR), a simple technique that concatenates document indices with referrals, i.e. text from other documents that cite or link to the given d…

cs.CL2023★ 2 cited

C-STS: Conditional Semantic Textual Similarity

Ameet Deshpande, Carlos E. Jimenez, Howard Chen +6

Semantic textual similarity (STS), a cornerstone task in NLP, measures the degree of similarity between a pair of sentences, and has broad application in fields such as information…

cs.CL2023★ 25 cited

Toxicity in ChatGPT: Analyzing Persona-assigned Language Models

Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit +2

Large language models (LLMs) have shown incredible capabilities and transcended the natural language processing (NLP) community, with adoption throughout many services like healthc…

cs.CL2023

SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification

Pranjal Aggarwal, Ameet Deshpande, Karthik Narasimhan

Extreme classification (XC) involves predicting over large numbers of classes (thousands to millions), with real-world applications like news article classification and e-commerce…