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Found 9 papers, 3 papers with code
Event-Event Relation Extraction using Probabilistic Box Embedding
To understand a story with multiple events, it is important to capture the proper relations across these events.
Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval
Moreover, when integrated with another retriever, CMC reranking can function as a virtually enhanced retriever.
Case-Based Reasoning Approach for Solving Financial Question Answering
To address this issue, we propose a novel approach to tackle numerical reasoning problems using case based reasoning (CBR), an artificial intelligence paradigm that provides problem solving guidance by offering similar cases (i. e. similar questions and corresponding logical programs).
Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation
In this paper, we present the discovery that a student model distilled from a few-shot prompted LLM can commonly generalize better than its teacher to unseen examples on such tasks.
Machine Reading Comprehension using Case-based Reasoning
Given a test question, CBR-MRC first retrieves a set of similar cases from a nonparametric memory and then predicts an answer by selecting the span in the test context that is most similar to the contextualized representations of answers in the retrieved cases.
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning
Meta-Adapters perform competitively with state-of-the-art few-shot learning methods that require full fine-tuning, while only fine-tuning 0. 6% of the parameters.
Improve Event Extraction via Self-Training with Gradient Guidance
Data scarcity has been the main factor that hinders the progress of event extraction.
Structured Energy Network as a dynamic loss function. Case study. A case study with multi-label Classification
The best version of SEAL that uses NCE ranking method achieves close to +2. 85, +2. 23 respective F1 point gain in average over cross-entropy and INFNET on the feature-based datasets, excluding one outlier that has an excessive gain of +50. 0 F1 points.
Case-based Reasoning for Natural Language Queries over Knowledge Bases
It is often challenging to solve a complex problem from scratch, but much easier if we can access other similar problems with their solutions -- a paradigm known as case-based reasoning (CBR).
Knowledge Base Question Answering
Natural Language Queries
+1
