Long Form Question Answering
17 papers with code • 0 benchmarks • 3 datasets
Long-form question answering is a task requiring elaborate and in-depth answers to open-ended questions.
Benchmarks
These leaderboards are used to track progress in Long Form Question Answering
Most implemented papers
ELI5: Long Form Question Answering
We introduce the first large-scale corpus for long-form question answering, a task requiring elaborate and in-depth answers to open-ended questions.
Hurdles to Progress in Long-form Question Answering
The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer.
SEMQA: Semi-Extractive Multi-Source Question Answering
Experimenting with several LLMs in various settings, we find this task to be surprisingly challenging, demonstrating the importance of QuoteSum for developing and studying such consolidation capabilities.
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
Query-based open-domain NLP tasks require information synthesis from long and diverse web results.
Controllable Generation from Pre-trained Language Models via Inverse Prompting
To tackle this challenge, we propose an innovative method, inverse prompting, to better control text generation.
D2S: Document-to-Slide Generation Via Query-Based Text Summarization
Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time-consuming.
LongForm: Effective Instruction Tuning with Reverse Instructions
We generate instructions via LLMs for human-written corpus examples using reverse instructions.
Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks
This paper proposes a novel framework named \textbf{Search-in-the-Chain} (SearChain) for the interaction between LLM and IR to solve the challenges.
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
We recruit annotators to search for relevant information using our interface and then answer questions.
Revisiting Sentence Union Generation as a Testbed for Text Consolidation
In this paper, we suggest revisiting the sentence union generation task as an effective well-defined testbed for assessing text consolidation capabilities, decoupling the consolidation challenge from subjective content selection.