4 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Humans Hallucinate Too: Language Models Identify and Correct Subjective Annotation Errors With Label-in-a-Haystack Prompts
Georgios Chochlakis, Peter Wu, Arjun Bedi +3
Modeling complex subjective tasks in Natural Language Processing, such as recognizing emotion and morality, is considerably challenging due to significant variation in human annota…
Larger Language Models Don't Care How You Think: Why Chain-of-Thought Prompting Fails in Subjective Tasks
Georgios Chochlakis, Niyantha Maruthu Pandiyan, Kristina Lerman +1
In-Context Learning (ICL) in Large Language Models (LLM) has emerged as the dominant technique for performing natural language tasks, as it does not require updating the model para…
Aggregation Artifacts in Subjective Tasks Collapse Large Language Models' Posteriors
Georgios Chochlakis, Alexandros Potamianos, Kristina Lerman +1
In-context Learning (ICL) has become the primary method for performing natural language tasks with Large Language Models (LLMs). The knowledge acquired during pre-training is cruci…
The Strong Pull of Prior Knowledge in Large Language Models and Its Impact on Emotion Recognition
Georgios Chochlakis, Alexandros Potamianos, Kristina Lerman +1
In-context Learning (ICL) has emerged as a powerful paradigm for performing natural language tasks with Large Language Models (LLM) without updating the models' parameters, in cont…