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20222026
most citedSWE-bench: Can Language Models Resolve Real-World GitHub Issues?

53 citations · 98 across the 11 of their papers we have counts for

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cs.CL2025

IMPersona: Evaluating Individual Level LM Impersonation

Quan Shi, Carlos E. Jimenez, Stephen Dong +4

As language models achieve increasingly human-like capabilities in conversational text generation, a critical question emerges: to what extent can these systems simulate the charac…

cs.CL2024★ 2 cited

SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains?

John Yang, Carlos E. Jimenez, Alex L. Zhang +10

Autonomous systems for software engineering are now capable of fixing bugs and developing features. These systems are commonly evaluated on SWE-bench (Jimenez et al., 2024a), which…

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★ 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.CL2022★ 2 cited

CARETS: A Consistency And Robustness Evaluative Test Suite for VQA

Carlos E. Jimenez, Olga Russakovsky, Karthik Narasimhan

We introduce CARETS, a systematic test suite to measure consistency and robustness of modern VQA models through a series of six fine-grained capability tests. In contrast to existi…