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Long Form Question Answering

Long-form question answering is a task requiring elaborate and in-depth answers to open-ended questions.

Papers

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Showing 1–25 of 61 papers

TitleStatusHype
ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language ModelsCode2
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking TechniquesCode2
Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingCode2
WebCPM: Interactive Web Search for Chinese Long-form Question AnsweringCode2
LongForm: Effective Instruction Tuning with Reverse InstructionsCode2
OLAPH: Improving Factuality in Biomedical Long-form Question AnsweringCode1
CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systemsCode1
Attribute First, then Generate: Locally-attributable Grounded Text GenerationCode1
ALaRM: Align Language Models via Hierarchical Rewards ModelingCode1
SEMQA: Semi-Extractive Multi-Source Question AnsweringCode1
Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference OptimizationCode1
A Critical Evaluation of Evaluations for Long-form Question AnsweringCode1
Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive TasksCode1
D2S: Document-to-Slide Generation Via Query-Based Text SummarizationCode1
Controllable Generation from Pre-trained Language Models via Inverse PromptingCode1
Hurdles to Progress in Long-form Question AnsweringCode1
ELI5: Long Form Question AnsweringCode1
GenerationPrograms: Fine-grained Attribution with Executable ProgramsCode0
Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs—0
LaMP-QA: A Benchmark for Personalized Long-form Question Answering—0
Atomic Consistency Preference Optimization for Long-Form Question AnsweringCode0
An Empirical Study of Evaluating Long-form Question AnsweringCode0
MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration—0
Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution—0
On the Influence of Context Size and Model Choice in Retrieval-Augmented Generation SystemsCode0
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