206 citations · 510 across the 27 of their papers we have counts for
25 papers · 1 filter
Can Large Language Models Generalize Procedures Across Representations?
Fangru Lin, Valentin Hofmann, Xingchen Wan +4
Large language models (LLMs) are trained and tested extensively on symbolic representations such as code and graphs, yet real-world user tasks are often specified in natural langua…
Quantifying Compositionality of Classic and State-of-the-Art Embeddings
Zhijin Guo, Chenhao Xue, Zhaozhen Xu +4
For language models to generalize correctly to novel expressions, it is critical that they exploit access compositional meanings when this is justified. Even if we don't know what…
ClimateViz: A Benchmark for Statistical Reasoning and Fact Verification on Scientific Charts
Ruiran Su, Jiasheng Si, Zhijiang Guo +1
Scientific fact-checking has mostly focused on text and tables, overlooking scientific charts, which are key for presenting quantitative evidence and statistical reasoning. We intr…
Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups
Felix Drinkall, Stefan Zohren, Michael McMahon +1
Macroeconomic fluctuations and the narratives that shape them form a mutually reinforcing cycle: public discourse can spur behavioural changes leading to economic shifts, which the…
When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks
Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
Large language models (LLMs) have shown remarkable success in language modelling due to scaling laws found in model size and the hidden dimension of the model's text representation…
Derivational Morphology Reveals Analogical Generalization in Large Language Models
Valentin Hofmann, Leonie Weissweiler, David Mortensen +2
What mechanisms underlie linguistic generalization in large language models (LLMs)? This question has attracted considerable attention, with most studies analyzing the extent to wh…