18 papers
Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning
Maggie Mi, Golzar Atefi, Atsuki Yamaguchi +3
Idioms can be analysed in terms of their decomposability, the extent to which constituent meanings contribute to the figurative whole. Decomposability is thought to predict syntact…
Frame In, Frame Out: Measuring Framing Bias in LLM-Generated News Summaries
Valeria Pastorino, Nafise Sadat Moosavi
News headlines and summaries shape how events are interpreted through selective emphasis and omission, a phenomenon commonly referred to as framing. Large language models are now r…
Hidden Failures in Robustness: Why Supervised Uncertainty Quantification Needs Better Evaluation
Joe Stacey, Hadas Orgad, Kentaro Inui +2
Recent work has shown that the hidden states of large language models contain signals useful for uncertainty estimation and hallucination detection, motivating a growing interest i…
Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization
Ian W. Kennedy, Nafise Sadat Moosavi
Additive quantization enables extreme LLM compression with O(1) lookup-table dequantization, making it attractive for edge deployment. Yet at 2-bit precision, it often fails catast…
Decoding News Narratives: A Critical Analysis of Large Language Models in Framing Detection
Valeria Pastorino, Jasivan A. Sivakumar, Nafise Sadat Moosavi
The growing complexity and diversity of news coverage have made framing analysis a crucial yet challenging task in computational social science. Traditional approaches, including m…
Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation
Steffen Eger, Yong Cao, Jennifer D'Souza +11
With the advent of large multimodal language models, science is now at a threshold of an AI-based technological transformation. An emerging ecosystem of models and tools aims to su…