WebQuestions

Overview edit

Variants: WebQuestions

Associated Benchmarks

This dataset is used in 3 benchmarks:

• Question Answering - Metrics: EM, F1
• Open-Domain Question Answering - Metrics: Exact Match
• KG-to-Text Generation - Metrics: BLEU, METEOR, ROUGE

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models (2024) -
• DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines (2023) -
• Tree of Thoughts: Deliberate Problem Solving with Large Language Models (2023) -
• PaLM 2 Technical Report (2023) -
• FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference (2022) -
• FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering (2022) -
• Measuring and Narrowing the Compositionality Gap in Language Models (2022) -
• ReAct: Synergizing Reasoning and Acting in Language Models (2022) -
• PaLM: Scaling Language Modeling with Pathways (2022) -
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (2022) -
• GLaM: Efficient Scaling of Language Models with Mixture-of-Experts (2021) -
• JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs (2021) -
• End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering (2021) -
• UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering (2020) -
• Language Models are Few-Shot Learners (2020) -
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020) -
• Toward Subgraph-Guided Knowledge Graph Question Generation with Graph Neural Networks (2020) -
• Dense Passage Retrieval for Open-Domain Question Answering (2020) -
• REALM: Retrieval-Augmented Language Model Pre-Training (2020) -
• Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (2019) -