Search Results for author:
Found 5 papers, 3 papers with code
Do Llamas Work in English? On the Latent Language of Multilingual Transformers
Tracking intermediate embeddings through their high-dimensional space reveals three distinct phases, whereby intermediate embeddings (1) start far away from output token embeddings; (2) already allow for decoding a semantically correct next token in the middle layers, but give higher probability to its version in English than in the input language; (3) finally move into an input-language-specific region of the embedding space.
Evaluating Language Model Agency through Negotiations
We introduce an approach to evaluate language model (LM) agency using negotiation games.
Prevalence and prevention of large language model use in crowd work
We show that the use of large language models (LLMs) is prevalent among crowd workers, and that targeted mitigation strategies can significantly reduce, but not eliminate, LLM use.
Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks
With the widespread adoption of LLMs, human gold--standard annotations are key to understanding the capabilities of LLMs and the validity of their results.
Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Science
Large Language Models (LLMs) have democratized synthetic data generation, which in turn has the potential to simplify and broaden a wide gamut of NLP tasks.
