5 citations · 7 across the 4 of their papers we have counts for
4 papers
Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models
Lin Zheng, Vasilisa Bashlovkina, Timothy Dozat +3
Tokenizer-free language models eliminate the tokenizer step of the language modeling pipeline by operating directly on bytes; patch-based variants further aggregate contiguous byte…
Trusted Source Alignment in Large Language Models
Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews +4
Large language models (LLMs) are trained on web-scale corpora that inevitably include contradictory factual information from sources of varying reliability. In this paper, we propo…
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding
Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang +2
We study the ability of transformer-based language models (LMs) to understand social media language. Social media (SM) language is distinct from standard written language, yet exis…
What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis
Xiang Deng, Vasilisa Bashlovkina, Feng Han +2
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. The resu…