4 citations · 6 across the 3 of their papers we have counts for
4 papers
metaTextGrad: Automatically optimizing language model optimizers
Guowei Xu, Mert Yuksekgonul, Carlos Guestrin +1
Large language models (LLMs) are increasingly used in learning algorithms, evaluations, and optimization tasks. Recent studies have shown that using LLM-based optimizers to automat…
A ghost mechanism: An analytical model of abrupt learning in recurrent networks
Fatih Dinc, Ege Cirakman, Bariscan Kurtkaya +4
Abrupt learning is a common phenomenon in recurrent neural networks (RNNs) trained on working memory tasks. In such cases, the networks develop transient slow regions in state spac…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…
Diversity of Thought Improves Reasoning Abilities of LLMs
Ranjita Naik, Varun Chandrasekaran, Mert Yuksekgonul +2
Large language models (LLMs) are documented to struggle in settings that require complex reasoning. Nevertheless, instructing the model to break down the problem into smaller reaso…