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Found 5 papers, 2 papers with code
Calibrated Seq2seq Models for Efficient and Generalizable Ultra-fine Entity Typing
In this paper, we present CASENT, a seq2seq model designed for ultra-fine entity typing that predicts ultra-fine types with calibrated confidence scores.
EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Models
In this paper, we propose an overarching framework for event semantic processing, encompassing understanding, reasoning, and prediction, along with their fine-grained aspects.
Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering
Existing work on augmenting question answering (QA) models with external knowledge (e. g., knowledge graphs) either struggle to model multi-hop relations efficiently, or lack transparency into the model's prediction rationale.
Towards a Unified End-to-End Approach for Fully Unsupervised Cross-Lingual Sentiment Analysis
Cross-lingual sentiment analysis (CLSA) aims to improve the performance on these languages by leveraging annotated data from other languages.
Learning Bilingual Sentiment-Specific Word Embeddings without Cross-lingual Supervision
Our method only requires a sentiment corpus in the source language and pretrained monolingual word embeddings of both languages.
