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20162026
most citedGemma 3 Technical Report

65 citations · 206 across the 55 of their papers we have counts for

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Showing 2025 · cs.CLShow all

8 papers · 2 filters

cs.CL2025

HACK: Hallucinations Along Certainty and Knowledge Axes

Adi Simhi, Jonathan Herzig, Itay Itzhak +7

Hallucinations in LLMs present a critical barrier to their reliable usage. Existing research usually categorizes hallucination by their external properties rather than by the LLMs'…

cs.CL2025

ManagerBench: Evaluating the Safety-Pragmatism Trade-off in Autonomous LLMs

Adi Simhi, Jonathan Herzig, Martin Tutek +3

As large language models (LLMs) evolve from conversational assistants into autonomous agents, evaluating the safety of their actions becomes critical. Prior safety benchmarks have…

cs.CL2025★ 49 cited

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…

cs.CL2025

DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs

Arie Cattan, Alon Jacovi, Ori Ram +6

Retrieval Augmented Generation (RAG) is a commonly used approach for enhancing large language models (LLMs) with relevant and up-to-date information. However, the retrieved sources…

cs.CL2025

Unblocking Fine-Grained Evaluation of Detailed Captions: An Explaining AutoRater and Critic-and-Revise Pipeline

Brian Gordon, Yonatan Bitton, Andreea Marzoca +4

Large Vision-Language Models (VLMs) now generate highly detailed, paragraphlength image captions, yet evaluating their factual accuracy remains challenging. Current methods often m…

cs.CL2025

MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs

Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu +3

A critical component in the trustworthiness of LLMs is reliable uncertainty communication, yet LLMs often use assertive language when conveying false claims, leading to over-relian…