LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.

This repository collects an extensive list of awesome papers about Story Generation / Storytelling, exclusively focusing on the era of Large Language Models (LLMs).

PaL: Program-Aided Language Models (ICML 2023)

Interpretability for sequence generation models 🐛 🔍

A method to fix GPT-3 after deployment with user feedback, without re-training.

Code for "Aligning Linguistic Words and Visual Semantic Units for Image Captioning", ACM MM 2019

XLNet for generating language.

On Generating Extended Summaries of Long Documents

NAACL'19: "Jointly Optimizing Diversity and Relevance in Neural Response Generation"

UNION: An Unreferenced Metric for Evaluating Open-ended Story Generation

Benchmark for evaluating open-ended generation

Official code for the NAACL 2022 paper "Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation"

Design and build a chatbot using data from the Cornell Movie Dialogues corpus, using Keras

[AAAI'26 Oral] Official Implementation of STAR-1: Safer Alignment of Reasoning LLMs with 1K Data

Pre-trained models for our work on Temporal Graph Generation

Event based Sign-Language-Translation

Synthetic QA generation for long documents.

Multi-Figurative Language Generation (COLING 2022)

Pytorch version of Continuous Language Generative Flow (ACL 2021)

Using Machine Translation to "translate" non-humor into humor. Code for the paper "Humorous Headline Generation via Style Transfer" at FigLang 2020