papers

Publications (11)

cs.CL2016

Equation Parsing: Mapping Sentences to Grounded Equations

Subhro Roy, Shyam Upadhyay, Dan Roth

Identifying mathematical relations expressed in text is essential to understanding a broad range of natural language text from election reports, to financial news, to sport comment…

cs.CL2017

Mapping to Declarative Knowledge for Word Problem Solving

Subhro Roy, Dan Roth

Math word problems form a natural abstraction to a range of quantitative reasoning problems, such as understanding financial news, sports results, and casualties of war. Solving su…

cs.CL2021

Task-Oriented Dialogue as Dataflow Synthesis

Semantic Machines, Jacob Andreas, John Bufe +43

We describe an approach to task-oriented dialogue in which dialogue state is represented as a dataflow graph. A dialogue agent maps each user utterance to a program that extends th…

cs.CL2016

Solving General Arithmetic Word Problems

Subhro Roy, Dan Roth

This paper presents a novel approach to automatically solving arithmetic word problems. This is the first algorithmic approach that can handle arithmetic problems with multiple ste…

cs.CL2023

InstructExcel: A Benchmark for Natural Language Instruction in Excel

Justin Payan, Swaroop Mishra, Mukul Singh +7

With the evolution of Large Language Models (LLMs) we can solve increasingly more complex NLP tasks across various domains, including spreadsheets. This work investigates whether L…

cs.CL2022

ZEROTOP: Zero-Shot Task-Oriented Semantic Parsing using Large Language Models

Dheeraj Mekala, Jason Wolfe, Subhro Roy

We explore the use of large language models (LLMs) for zero-shot semantic parsing. Semantic parsing involves mapping natural language utterances to task-specific meaning representa…

cs.CL2022

Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation

Kevin Yang, Olivia Deng, Charles Chen +3

We introduce a novel setup for low-resource task-oriented semantic parsing which incorporates several constraints that may arise in real-world scenarios: (1) lack of similar datase…

cs.CL2024

BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing

Subhro Roy, Sam Thomson, Tongfei Chen +4

Recent work has shown that generation from a prompted or fine-tuned language model can perform well at semantic parsing when the output is constrained to be a valid semantic repres…

cs.CL2021

Constrained Language Models Yield Few-Shot Semantic Parsers

Richard Shin, Christopher H. Lin, Sam Thomson +7

We explore the use of large pretrained language models as few-shot semantic parsers. The goal in semantic parsing is to generate a structured meaning representation given a natural…

cs.CL2016

Unit Dependency Graph and its Application to Arithmetic Word Problem Solving

Subhro Roy, Dan Roth

Math word problems provide a natural abstraction to a range of natural language understanding problems that involve reasoning about quantities, such as interpreting election result…

cs.CG2014

Approximating the Maximum Overlap of Polygons under Translation

Sariel Har-Peled, Subhro Roy

Let and be two simple polygons in the plane of total complexity , each of which can be decomposed into at most convex parts. We present an -approxim…