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Found 11 papers, 2 papers with code
NeSy is alive and well: A LLM-driven symbolic approach for better code comment data generation and classification
We present a neuro-symbolic (NeSy) workflow combining a symbolic-based learning technique with a large language model (LLM) agent to generate synthetic data for code comment classification in the C programming language.
PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering Grounding
The Scholarly Question Answering over Linked Data (Scholarly QALD) at The International Semantic Web Conference (ISWC) 2023 challenge presents two sub-tasks to tackle question answering (QA) over knowledge graphs (KGs).
A ML-LLM pairing for better code comment classification
The "Information Retrieval in Software Engineering (IRSE)" at FIRE 2023 shared task introduces code comment classification, a challenging task that pairs a code snippet with a comment that should be evaluated as either useful or not useful to the understanding of the relevant code.
The Path to Autonomous Learners
In this paper, we present a new theoretical approach for enabling domain knowledge acquisition by intelligent systems.
Yseop at FinSim-3 Shared Task 2021: Specializing Financial Domain Learning with Phrase Representations
In this paper, we present our approaches for the FinSim-3 Shared Task 2021: Learning Semantic Similarities for the Financial Domain.
Financial Document Causality Detection Shared Task (FinCausal 2020)
We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results.
Data Processing and Annotation Schemes for FinCausal Shared Task
This document explains the annotation schemes used to label the data for the FinCausal Shared Task (Mariko et al., 2020).
Yseop at SemEval-2020 Task 5: Cascaded BERT Language Model for Counterfactual Statement Analysis
In this paper, we explore strategies to detect and evaluate counterfactual sentences.
