2 citations · 4 across the 7 of their papers we have counts for
8 papers
On Mitigating Code LLM Hallucinations with API Documentation
Nihal Jain, Robert Kwiatkowski, Baishakhi Ray +2
In this study, we address the issue of API hallucinations in various software engineering contexts. We introduce CloudAPIBench, a new benchmark designed to measure API hallucinatio…
A Static Evaluation of Code Completion by Large Language Models
Hantian Ding, Varun Kumar, Yuchen Tian +9
Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to evaluate…
On the Origins of Self-Modeling
Robert Kwiatkowski, Yuhang Hu, Boyuan Chen +1
Self-Modeling is the process by which an agent, such as an animal or machine, learns to create a predictive model of its own dynamics. Once captured, this self-model can then allow…
Full-Body Visual Self-Modeling of Robot Morphologies
Boyuan Chen, Robert Kwiatkowski, Carl Vondrick +1
Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to c…
Visual Perspective Taking for Opponent Behavior Modeling
Boyuan Chen, Yuhang Hu, Robert Kwiatkowski +2
In order to engage in complex social interaction, humans learn at a young age to infer what others see and cannot see from a different point-of-view, and learn to predict others' p…
Zero Shot Learning on Simulated Robots
Robert Kwiatkowski, Hod Lipson
In this work we present a method for leveraging data from one source to learn how to do multiple new tasks. Task transfer is achieved using a self-model that encapsulates the dynam…
Agent Embeddings: A Latent Representation for Pole-Balancing Networks
Oscar Chang, Robert Kwiatkowski, Siyuan Chen +1
We show that it is possible to reduce a high-dimensional object like a neural network agent into a low-dimensional vector representation with semantic meaning that we call agent em…
Gradient Normalization & Depth Based Decay For Deep Learning
Robert Kwiatkowski, Oscar Chang
In this paper we introduce a novel method of gradient normalization and decay with respect to depth. Our method leverages the simple concept of normalizing all gradients in a deep…