emnlp2023

WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.

A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation"

EMNLP 2023 Papers: Explore cutting-edge research from EMNLP 2023, the premier conference for advancing empirical methods in natural language processing. Stay updated on the latest in machine learning, deep learning, and natural language processing with code included. ⭐ support NLP!

Large Language Models are Temporal and Causal Reasoners for Video Question Answering (EMNLP 2023)

The implementation for EMNLP 2023 paper ”Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators“

Release repo for our work "Token Prediction as Implicit Classification to Identify LLM-Generated Text"

Visual and Embodied Concepts evaluation benchmark

Are foundation LMs multilingual knowledge bases? (EMNLP 2023)

Discovering Universal Geometry in Embeddings with ICA (Published in EMNLP 2023)

[EMNLP 2023] Semi-automatic Data Enhancement for Document-Level Relation Extraction with Distant Supervision from Large Language Models

The code implementation of the paper CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Low Resource With Contrastive Learning from XJTU.

HFMRE: Constructing Huffman Tree in Bags to Find Excellent Instances for Distantly Supervised Relation Extraction

This repository includes the code implementation of the paper Improving Pacing in Long-Form Story Planning by Yichen Wang, Kevin Yang, Xiaoming Liu, and Dan Klein.

[EMNLP 2023] FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization. Support BART, PEGASUS, T5, mT5, BioBART, etc.

[EMNLP'23 Oral] ReSee: Responding through Seeing Fine-grained Visual Knowledge in Open-domain Dialogue PyTorch Implementation

Improving word mover’s distance by leveraging self-attention matrix (Published in EMNLP 2023 Findings)

Source repository for Editing Common Sense in Transformers (EMNLP 2023)

[EMNLP2023] MixTEA: Semi-supervised Entity Alignment with Mixture Teaching

Data and codes for the EMNLP 2023 paper 'LLMs – the Good, the Bad or the Indispensable?: A Use Case on Legal Statute Prediction and Legal Judgment Prediction on Indian Court Cases'

Repo for EMNLP finding Paper "Long-Range Language Modeling with Selective Cache"