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Found 6 papers, 1 papers with code
LiPO: Listwise Preference Optimization through Learning-to-Rank
In this work, we formulate the LM alignment as a listwise ranking problem and describe the Listwise Preference Optimization (LiPO) framework, where the policy can potentially learn more effectively from a ranked list of plausible responses given the prompt.
Trusted Source Alignment in Large Language Models
Large language models (LLMs) are trained on web-scale corpora that inevitably include contradictory factual information from sources of varying reliability.
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding
We study the ability of transformer-based language models (LMs) to understand social media language.
What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis
Market sentiment analysis on social media content requires knowledge of both financial markets and social media jargon, which makes it a challenging task for human raters.
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
In this paper, we propose a new model inductive bias that learns a subword tokenization end-to-end as part of the model.
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Paraphrase Identification
on Quora Question Pairs
A Generative Approach to Titling and Clustering Wikipedia Sections
We evaluate the performance of transformer encoders with various decoders for information organization through a new task: generation of section headings for Wikipedia articles.
