2 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
Towards Fair and Comprehensive Evaluation of Routers in Collaborative LLM Systems
Wanxing Wu, He Zhu, Yixia Li +7
Large language models (LLMs) have achieved success, but cost and privacy constraints necessitate deploying smaller models locally while offloading complex queries to cloud-based mo…
ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
Chenchen Zhang, Yuhang Li, Can Xu +17
The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a crit…
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models
Maurice Diesendruck, Jianzhe Lin, Shima Imani +3
When LLMs perform zero-shot inference, they typically use a prompt with a task specification, and generate a completion. However, there is no work to explore the possibility of the…
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang +2
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid…