Nealcly

InstructionWild

Llama-X

Open Academic Research on Improving LLaMA to SOTA LLM

CTCWordBeamSearch

Connectionist Temporal Classification (CTC) decoder with dictionary and language model.

Chinese-LLaMA-Alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

Megatron-LM

Ongoing research training transformer models at scale

SciTweets

CHEF

The source code of paper "CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking"

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

HMT

Source code for ICLR 2023 spotlight paper "Hidden Markov Transformer for Simultaneous Machine Translation"

text-generation-inference

Large Language Model Text Generation Inference

InteractiveTextGeneration

LLM-Augmenter

llama

Inference code for Llama models

Automated-Fact-Checking-Resources

Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).

detect-gpt

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature

NewsEdits

neural-Jacana

This is the code for neural-Jacana aligner, and the data for MultiMWA dataset.

genius

💡GENIUS – generating text using sketches! A strong text generation & data augmentation tool.

seq2seq-corenlp

ParaScore

m2scorer

MaxMatch (M^2) Scorer - Evaluation program for grammatical error correction systems.

editpro

Learning to Model Editing Processes

kilogram

The KiloGram Tangrams dataset

EditScorer

The code for EMNLP2022 paper "Improved grammatical error correction by ranking elementary edits"

following-instructions-human-feedback

CoSDA-ML

CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP

Cross-Align

EMNLP2022 "Cross-Align: Modeling Deep Cross-lingual Interactions for Word Alignment"

NMLA-NAT

Code for NeurIPS 2022 Spotlight paper " Non-Monotonic Latent Alignments for CTC-Based Non-Autoregressive Machine Translation"

GLUE-X

We leverage 14 datasets as OOD test data and conduct evaluations on 8 NLU tasks over 21 popularly used models. Our findings confirm that the OOD accuracy in NLP tasks needs to be paid more attention to since the significant performance decay compared to ID accuracy has been found in all settings.

UniSumm

UNISUMM: Unified Few-shot Summarization with Multi-Task Pre-Training and Prefix-Tuning