Large Language Model Evaluation on Financial Benchmarks
Bing Zhang, Mikio Takeuchi, et al.
ICAIF 2024
This paper presents a new method for resolving lexical (word sense) ambiguities inherent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an example-base, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.
Bing Zhang, Mikio Takeuchi, et al.
ICAIF 2024
Imran Nasim, Melanie Weber
SCML 2024
Rocco Langone, Carlos Alzate, et al.
SSCI 2013
Daniel Karl I. Weidele, Hendrik Strobelt, et al.
SysML 2019