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Answer Selection
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Answer Selection is the task of identifying the correct answer to a question from a pool of candidate answers. This task can be formulated as a classification or a ranking problem.
Source: Learning Analogy-Preserving Sentence Embeddings for Answer Selection
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Could Thinking Multilingually Empower LLM Reasoning?
Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection
Evaluating Answer Reranking Strategies in Time-sensitive Question Answering
FANS -- Formal Answer Selection for Natural Language Math Reasoning Using Lean4
SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
Zero-Shot End-To-End Spoken Question Answering In Medical Domain
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models
Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks
HGOT: Hierarchical Graph of Thoughts for Retrieval-Augmented In-Context Learning in Factuality Evaluation
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Enhancing Answer Selection in Community Question Answering with Pre-trained and Large Language Models
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset
Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answering
SQUARE: Automatic Question Answering Evaluation using Multiple Positive and Negative References
Solving Math Word Problem with Problem Type Classification
Abstracting Concept-Changing Rules for Solving Raven's Progressive Matrix Problems
Intent-calibrated Self-training for Answer Selection in Open-domain Dialogues
Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge
Getting MoRE out of Mixture of Language Model Reasoning Experts
Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement
RLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm
Leveraging Large Language Models for Multiple Choice Question Answering
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs
Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection
Paragraph-based Transformer Pre-training for Multi-Sentence Inference
Solution of DeBERTaV3 on CommonsenseQA
CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues
DEIM: An effective deep encoding and interaction model for sentence matching
Question-Answer Sentence Graph for Joint Modeling Answer Selection
Double Retrieval and Ranking for Accurate Question Answering
OpenQA: Hybrid QA System Relying on Structured Knowledge Base as well as Non-structured Data
PerCQA: Persian Community Question Answering Dataset
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph
A Multi-Size Neural Network with Attention Mechanism for Answer Selection
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