David Wang — accepted AI-conference papers

2023

MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language Models

Deepak Nathani, David Wang, Liangming Pan, William Yang Wang

EMNLP 2023long main

Language Models (LMs) have shown impressive performance in various natural language tasks. However, when it comes to natural language reasoning, LMs still face challenges such as hallucination, generating incorrect intermediate reasoning steps, and making mathematical errors. Recent research has foc…

Cited by 0 Source ↗code ↗Scholar ↗

2019

Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter

Michael Danielczuk, Andrey Kurenkov, Ashwin Balakrishna, Matthew Matl, David Wang, Roberto Martín-Martín +3

ICRA 2019poster

When operating in unstructured environments such as warehouses, homes, and retail centers, robots are frequently required to interactively search for and retrieve specific objects from cluttered bins, shelves, or tables. Mechanical Search describes the class of tasks where the goal is to locate and…

Cited by 141 Source ↗Scholar ↗