most citedGemma 4 Technical Report

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

collaborators

7 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.CL2025

Tomato, Tomahto, Tomate: Do Multilingual Language Models Understand Based on Subword-Level Semantic Concepts?

Crystina Zhang, Jing Lu, Vinh Q. Tran +3

Human understanding of text depends on general semantic concepts of words rather than their superficial forms. To what extent does our human intuition transfer to language models?…

cs.CL2025

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation

Sangmin Bae, Yujin Kim, Reza Bayat +8

Scaling language models unlocks impressive capabilities, but the accompanying computational and memory demands make both training and deployment expensive. Existing efficiency effo…

cs.LG2025

Fast Inference via Hierarchical Speculative Decoding

Clara Mohri, Haim Kaplan, Tal Schuster +2

Transformer language models generate text autoregressively, making inference latency proportional to the number of tokens generated. Speculative decoding reduces this latency witho…

stat.ME2025

Conformal Risk Control

Anastasios N. Angelopoulos, Stephen Bates, Adam Fisch +2

We extend conformal prediction to control the expected value of any monotone loss function. The algorithm generalizes split conformal prediction together with its coverage guarante…

cs.CL2025

Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA

Sangmin Bae, Adam Fisch, Hrayr Harutyunyan +3

Large language models (LLMs) are expensive to deploy. Parameter sharing offers a possible path towards reducing their size and cost, but its effectiveness in modern LLMs remains fa…