353 citations · 1.2k across the 32 of their papers we have counts for
32 papers
TPV: Parameter Perturbations Through the Lens of Test Prediction Variance
Devansh Arpit
We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifying framework for analyzing post-trainin…
Causal Layering via Conditional Entropy
Itai Feigenbaum, Devansh Arpit, Huan Wang +5
Causal discovery aims to recover information about an unobserved causal graph from the observable data it generates. Layerings are orderings of the variables which place causes bef…
Editing Arbitrary Propositions in LLMs without Subject Labels
Itai Feigenbaum, Devansh Arpit, Huan Wang +5
Large Language Model (LLM) editing modifies factual information in LLMs. Locate-and-Edit (L\&E) methods accomplish this by finding where relevant information is stored within the n…
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
Zhiwei Liu, Weiran Yao, Jianguo Zhang +12
The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs). An LAA is able to generate actions with its core…
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles +12
Recent months have seen the emergence of a powerful new trend in which large language models (LLMs) are augmented to become autonomous language agents capable of performing objecti…
REX: Rapid Exploration and eXploitation for AI Agents
Rithesh Murthy, Shelby Heinecke, Juan Carlos Niebles +12
In this paper, we propose an enhanced approach for Rapid Exploration and eXploitation for AI Agents called REX. Existing AutoGPT-style techniques have inherent limitations, such as…