5 accepted papers
Humans increasingly query Large Language Models (LLMs) to accomplish personal tasks according to their individual preferences. However, these preferences are often unconsciously veiled during conversation. To address this, LLMs have to elicit human preferences through multi-turn dialogue, where task
Discourse Representation Structure (DRS) is an innovative semantic representation designed to capture the meaning of texts with arbitrary lengths across languages. The semantic representation parsing is essential for achieving natural language understanding through logical forms. Nevertheless, the p…
Semantic parsing is the task of translating natural language into a structured, formal semantic representation that can be interpreted by machines. These semantic representations are organized with complex structures. While various models have been developed for semantic parsing, there has been limi…
The growing concerns and regulations surrounding the protection of user data privacy have necessitated decentralized training paradigms. To this end, federated learning (FL) is widely studied in user-related natural language processing (NLP). However, it suffers from several critical limitations inc…
We propose neural models to generate text from formal meaning representations based on Discourse Representation Structures (DRSs). DRSs are document-level representations which encode rich semantic detail pertaining to rhetorical relations, presupposition, and co-reference within and across sentence…