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

297 citations · 436 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2026

"A Second Set of Eyes": The Process and Challenges of Software Documentation Review

Avinash Bhat, Ian Arawjo, Disha Shrivastava +1

Organizations assign documentation work to technical writers, yet the knowledge required to produce it is distributed across developers, managers, and other practitioners. Prior wo…

cs.CL2025

The Bias is in the Details: An Assessment of Cognitive Bias in LLMs

R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3

As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…

cs.CL2024

Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in Thai

Parinthapat Pengpun, Can Udomcharoenchaikit, Weerayut Buaphet +1

We present a synthetic data approach for instruction-tuning large language models (LLMs) for low-resource languages in a data-efficient manner, specifically focusing on Thai. We id…

cs.LG2024★ 7 cited

Training Language Models to Self-Correct via Reinforcement Learning

Aviral Kumar, Vincent Zhuang, Rishabh Agarwal +15

Self-correction is a highly desirable capability of large language models (LLMs), yet it has consistently been found to be largely ineffective in modern LLMs. Current methods for t…

cs.HC2024★ 132 cited

A Design Space for Intelligent and Interactive Writing Assistants

Mina Lee, Katy Ilonka Gero, John Joon Young Chung +33

In our era of rapid technological advancement, the research landscape for writing assistants has become increasingly fragmented across various research communities. We seek to addr…

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…