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20242026
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cs.CL2026

Revising RVL-CDIP: Quantifying Errors and Test-Train Overlap

Stefan Larson, Attila Nagy, Sam Desai +8

RVL-CDIP is a popular dataset for benchmarking document classifiers. However, the dataset contains ample amounts of label errors as well as non-trivial amounts of test-train overla…

cs.CL2025

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42

The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…

cs.CL2025

MKA: Leveraging Cross-Lingual Consensus for Model Abstention

Sharad Duwal

Reliability of LLMs is questionable even as they get better at more tasks. A wider adoption of LLMs is contingent on whether they are usably factual. And if they are not, on whethe…

cs.CL2024

Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali

Sharad Duwal, Suraj Prasai, Suresh Manandhar

Continual learning has emerged as an important research direction due to the infeasibility of retraining large language models (LLMs) from scratch in the event of new data availabi…

cs.CL2024

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Angelika Romanou, Negar Foroutan, Anna Sotnikova +56

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…