most citedApple Intelligence Foundation Language Models

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.AI20264 cited

Apple Intelligence Foundation Language Models

Tom Gunter, Zirui Wang, Chong Wang +152

We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large serv…

cs.LG2026

COMPASS: Benchmarking Constrained Optimization in LLM Agents

Tian Qin, Felix Bai, Ting-Yao Hu +8

Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shopping, and scheduling, they must…

cs.LG2025

Apple Intelligence Foundation Language Models: Tech Report 2025

Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395

We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model opti…

cs.CL2025

MR. Judge: Multimodal Reasoner as a Judge

Renjie Pi, Felix Bai, Qibin Chen +4

The paradigm of using Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) as evaluative judges has emerged as an effective approach in RLHF and inference-time…

cs.CL2025

ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities

Jiarui Lu, Thomas Holleis, Yizhe Zhang +9

Recent large language models (LLMs) advancements sparked a growing research interest in tool assisted LLMs solving real-world challenges, which calls for comprehensive evaluation o…