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a-hierarchical-latent-structure-for-variational-conversation-modeling

PyTorch Implementation of "A Hierarchical Latent Structure for Variational Conversation Modeling" (NAACL 2018 Oral)

acl-pub

Place to collect updated documents needed for ACL publications.

adapter-transformers

Huggingface Transformers + Adapters = ❤️

ai-tutorials

alexa-prize-topical-chat-dataset

A knowledge-grounded human-human dataset of open-domain conversations.

alexa-teacher-models

allentune

Hyperparameter Search for AllenNLP

alpaca-lora

Instruct-tune LLaMA on consumer hardware

amti

A Mechanical Turk Interface (amti) 🤖

artificial-intelligence-class.github.io

arxiv-latex-cleaner

arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv

asset

A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations

attentionexplanation

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

autocrit

A repository for transformer critique learning and generation

autolabel

Label, clean and enrich text datasets with LLMs.

awesome-aws-research

A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources for Academic Researchers new to AWS

beamdream

bertviz

Tool for visualizing BERT's self-attention layers

beta-stacy-bootstrap

Programs to replicate the analyses of the paper "A general Bayesian bootstrap for censored data based on the beta-Stacy process".

binarytree

Python Library for Learning Binary Trees

binarytree_v_1.1.1

blink

Entity Linker solution

cc_net

Tools to download and cleanup Common Crawl data

cdac

Contextual Dialogue Act Classification for Open-DomainConversational Agents

chaosnli

[EMNLP 2020] Collective HumAn OpinionS on Natural Language Inference Data

charliecloud

Lightweight user-defined software stacks for high-performance computing.

chateval

Public evaluation tool for non task driven neural open domain chatbots

chatevaluationplatform

circa

Circa (meaning ‘approximately’) dataset aims to help machine learning systems to solve the problem of interpreting indirect answers to polar questions. The dataset contains pairs of yes/no questions and indirect answers, together with annotations for the interpretation of the answer. The data is collected in 10 different social conversation situations (eg. food preferences of a friend).