Natural Language Processing › Generation ›

Text Generation

4534 directly classified papers

Papers per year

Papers

FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking EMNLP 2024

Unveiling the Invisible: Captioning Videos with Metaphors EMNLP 2024

Private prediction for large-scale synthetic text generation EMNLP 2024

Contextualized Graph Representations for Generating Counter-Narratives against Hate Speech EMNLP 2024

MetaKP: On-Demand Keyphrase Generation EMNLP 2024

PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer EMNLP 2024

ExpertEase: A Multi-Agent Framework for Grade-Specific Document Simplification with Large Language Models EMNLP 2024

Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning EMNLP 2024

Exploring Hint Generation Approaches for Open-Domain Question Answering EMNLP 2024

VeriScore: Evaluating the factuality of verifiable claims in long-form text generation EMNLP 2024

DisGeM: Distractor Generation for Multiple Choice Questions with Span Masking EMNLP 2024

Introducing Spatial Information and a Novel Evaluation Scheme for Open-Domain Live Commentary Generation EMNLP 2024

R2AG: Incorporating Retrieval Information into Retrieval Augmented Generation EMNLP 2024

To Err Is Human, but Llamas Can Learn It Too EMNLP 2024

HyQE: Ranking Contexts with Hypothetical Query Embeddings EMNLP 2024

Multi-trait User Simulation with Adaptive Decoding for Conversational Task Assistants EMNLP 2024

Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis EMNLP 2024

LongForm: Effective Instruction Tuning with Reverse Instructions EMNLP 2024

Beyond Persuasion: Towards Conversational Recommender System with Credible Explanations EMNLP 2024

Atomic Self-Consistency for Better Long Form Generations EMNLP 2024

ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems NAACL 2024

Generating Uncontextualized and Contextualized Questions for Document-Level Event Argument Extraction NAACL 2024

How Far Can We Extract Diverse Perspectives from Large Language Models? EMNLP 2024

Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation EMNLP 2024

Comparing Two Model Designs for Clinical Note Generation; Is an LLM a Useful Evaluator of Consistency? NAACL 2024