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Found 10 papers, 6 papers with code
Detection of Puffery on the English Wikipedia
On Wikipedia, an online crowdsourced encyclopedia, volunteers enforce the encyclopedia’s editorial policies.
Evaluating Gender Bias Transfer from Film Data
We extend our analysis to a longitudinal study of bias in film dialogue over the last 110 years and find that continued pre-training on OpenSubtitles encodes additional bias into BERT.
To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing
NLP is in a period of disruptive change that is impacting our methodologies, funding sources, and public perception.
It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk
Minimum Bayes Risk (MBR) decoding is a method for choosing the outputs of a machine learning system based not on the output with the highest probability, but the output with the lowest risk (expected error) among multiple candidates.
Prompt2Model: Generating Deployable Models from Natural Language Instructions
In this paper, we propose Prompt2Model, a general-purpose method that takes a natural language task description like the prompts provided to LLMs, and uses it to train a special-purpose model that is conducive to deployment.
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs
We reflect on human and LLMs' different sensitivities to instructions, stress the importance of enabling human-facing safeguards for LLMs, and discuss the potential of training humans and LLMs with complementary skill sets.
SummQA at MEDIQA-Chat 2023:In-Context Learning with GPT-4 for Medical Summarization
For full-note summarization (Task B), we use a similar solution with k=1.
Unlimiformer: Long-Range Transformers with Unlimited Length Input
This kNN index can be kept on either the GPU or CPU memory and queried in sub-linear time; this way, we can index practically unlimited input sequences, while every attention head in every decoder layer retrieves its top-k keys, instead of attending to every key.
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation
Many recent advances in natural language generation have been fueled by training large language models on internet-scale data.
He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues
As a sample application, we demonstrate that applying perspective shifting to a dialogue summarization dataset (SAMSum) substantially improves the zero-shot performance of extractive news summarization models on this data.
