Automating discovery in mathematics and science will require sophisticated methods of
information extraction and abstract reasoning, including models that can convincingly …

Neural retrievers have been shown to be effective for math-aware search. Their ability to
cope with math symbol mismatches, to represent highly contextualized semantics, and to …

Sparse retrieval techniques can detect exact matches, but are inadequate for mathematical
texts, where the same information can be expressed as either text or math. The soft vector …

Previous studies have introduced a weakly-supervised paradigm for solving math word
problems requiring only the answer value annotation. While these methods search for …

One of the challenges of math information retrieval is the inherent ambiguity of mathematical
notation. The use of various notations, symbols, and conventions can lead to ambiguities in …

Answer retrieval for math questions is a challenging task due to the complex and structured
nature of mathematical expressions. In this paper, we combine a structure retriever and a …

This paper describes the participation of the Artificial Intelligence and Information Retrieval
(AIIR) Lab from the University of Southern Maine and the Laboratory of Artificial Intelligence …

Numerical reasoning plays a pivotal role in both the realm of natural language processing
(NLP) research and real-life applications. Numerical reasoning, as an integral component of …

The ever-increasing volume of web-based documents poses a challenge in efficiently
accessing specialized knowledge from domain-specific sources, requiring a profound …