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20232026
most citedGemma 3 Technical Report

65 citations · 69 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026★ 3 cited

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…

cs.CL2025

SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?

Senyu Li, Jiayi Wang, Felermino D. M. A. Ali +7

Evaluating machine translation (MT) quality for under-resourced African languages remains a significant challenge, as existing metrics often suffer from limited language coverage a…

cs.CL2025★ 65 cited

Gemma 3 Technical Report

Gemma Team, Aishwarya Kamath, Johan Ferret +209

We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision underst…

cs.CL2024

On the Role of Summary Content Units in Text Summarization Evaluation

Marcel Nawrath, Agnieszka Nowak, Tristan Ratz +13

At the heart of the Pyramid evaluation method for text summarization lie human written summary content units (SCUs). These SCUs are concise sentences that decompose a summary into…

cs.CL2023

The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics

Christoph Leiter, Juri Opitz, Daniel Deutsch +3

With an increasing number of parameters and pre-training data, generative large language models (LLMs) have shown remarkable capabilities to solve tasks with minimal or no task-rel…