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20192026
most citedGemma: Open Models Based on Gemini Research and Technology

238 citations · 805 across the 38 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees

S M Rafiuddin, Atriya Sen

Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…

cs.CL2025

Language Models May Verbatim Complete Text They Were Not Explicitly Trained On

Ken Ziyu Liu, Christopher A. Choquette-Choo, Matthew Jagielski +4

An important question today is whether a given text was used to train a large language model (LLM). A \emph{completion} test is often employed: check if the LLM completes a suffici…

cs.CL2024★ 21 cited

CodeGemma: Open Code Models Based on Gemma

CodeGemma Team, Heri Zhao, Jeffrey Hui +24

This paper introduces CodeGemma, a collection of specialized open code models built on top of Gemma, capable of a variety of code and natural language generation tasks. We release…

cs.CL2024

Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien +9

Memorization in language models is typically treated as a homogenous phenomenon, neglecting the specifics of the memorized data. We instead model memorization as the effect of a se…

cs.CL2024★ 238 cited

Gemma: Open Models Based on Gemini Research and Technology

Gemma Team, Thomas Mesnard, Cassidy Hardin +105

This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate stro…

cs.CL2024

Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks

R. Patrick Xian, Alex J. Lee, Satvik Lolla +4

The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…

cs.CL2023★ 10 cited

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Sneha Kudugunta, Isaac Caswell, Biao Zhang +8

We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-a…

cs.CL2023★ 25 cited

Are aligned neural networks adversarially aligned?

Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo +8

Large language models are now tuned to align with the goals of their creators, namely to be "helpful and harmless." These models should respond helpfully to user questions, but ref…

cs.CL2023★ 168 cited

PaLM 2 Technical Report

Rohan Anil, Andrew M. Dai, Orhan Firat +125

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 i…