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20232026
most citedGemma 2: Improving Open Language Models at a Practical Size

145 citations · 177 across the 26 of their papers we have counts for

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6 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.CL20263 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

The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality

Aileen Cheng, Alon Jacovi, Amir Globerson +62

We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually…

cs.CL2025

Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL

Joey Hong, Anca Dragan, Sergey Levine

Large language models (LLMs) excel in tasks like question answering and dialogue, but complex tasks requiring interaction, such as negotiation and persuasion, require additional lo…

cs.CL2024145 cited

Gemma 2: Improving Open Language Models at a Practical Size

Gemma Team, Morgane Riviere, Shreya Pathak +195

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In th…

cs.CL2024

Context Steering: Controllable Personalization at Inference Time

Jerry Zhi-Yang He, Sashrika Pandey, Mariah L. Schrum +1

To deliver high-quality, personalized responses, large language models (LLMs) must effectively incorporate context -- personal, demographic, and cultural information specific to an…