activity
20242026
most citedGemini 1.5: Unlocking multimodal understanding across millions of tokens of context

297 citations · 298 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Grad2Reward: From Sparse Judgment to Dense Rewards for Improving Open-Ended LLM Reasoning

Zheng Zhang, Ao Lu, Yuanhao Zeng +5

Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant breakthroughs in complex LLM reasoning within verifiable domains, such as mathematics and programmin…

cs.CV2025★ 1 cited

Why Text Prevails: Vision May Undermine Multimodal Medical Decision Making

Siyuan Dai, Lunxiao Li, Kun Zhao +6

With the rapid progress of large language models (LLMs), advanced multimodal large language models (MLLMs) have demonstrated impressive zero-shot capabilities on vision-language ta…

cs.CL2025

Ideology as a Problem: Lightweight Logit Steering for Annotator-Specific Alignment in Social Media Analysis

Wei Xia, Haowen Tang, Luozheng Li

LLMs internally organize political ideology along low-dimensional structures that are partially, but not fully aligned with human ideological space. This misalignment is systematic…

cs.CV2025

InteractiveOmni: A Unified Omni-modal Model for Audio-Visual Multi-turn Dialogue

Wenwen Tong, Hewei Guo, Dongchuan Ran +23

We introduce InteractiveOmni, a unified and open-source omni-modal large language model for audio-visual multi-turn interaction, ranging from 4B to 8B parameters, designed to lead…

cs.HC2024

ORES-Inspect: A technology probe for machine learning audits on enwiki

Zachary Levonian, Lauren Hagen, Lu Li +4

Auditing the machine learning (ML) models used on Wikipedia is important for ensuring that vandalism-detection processes remain fair and effective. However, conducting audits is ch…

cs.CL2024★ 297 cited

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Petko Georgiev, Ving Ian Lei +1132

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…