activity
20242026
most citedGemma 4 Technical Report

1 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL20261 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.NE20261 cited

AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization

Mert Cemri, Shubham Agrawal, Akshat Gupta +9

The paradigm of automated program generation is shifting from one-shot generation to inference-time search, where Large Language Models (LLMs) function as semantic mutation operato…

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.CL2025

LLMRank: Understanding LLM Strengths for Model Routing

Shubham Agrawal, Prasang Gupta

The rapid growth of large language models (LLMs) with diverse capabilities, latency and computational costs presents a critical deployment challenge: selecting the most suitable mo…

cs.LG2025

Challenging Gradient Boosted Decision Trees with Tabular Transformers for Fraud Detection at Booking.com

Sergei Krutikov, Bulat Khaertdinov, Rodion Kiriukhin +3

Transformer-based neural networks, empowered by Self-Supervised Learning (SSL), have demonstrated unprecedented performance across various domains. However, related literature sugg…

cs.CL2024

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…