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cs.CL2026
What LLM Forecasters Know but Don't Say: Probing Internal Representations for Calibration and Faithfulness
Raphaël Sarfati, Pratyush Ranjan Tiwari, Siddharth Boppana +3
Large language models fine-tuned for forecasting can be accurate yet poorly calibrated, and their chain-of-thought (CoT) reasoning may not faithfully reflect the evidence behind a…
cs.CL2026
Jacobian Scopes: token-level causal attributions in LLMs
Toni J. B. Liu, Baran ZadeoÄlu, Nicolas Boullé +3
Large language models (LLMs) make next-token predictions based on clues present in their context, such as semantic descriptions and in-context examples. Yet, elucidating which prio…
cs.CL2025
What's in a prompt? Language models encode literary style in prompt embeddings
Raphaël Sarfati, Haley Moller, Toni J. B. Liu +2
Large language models use high-dimensional latent spaces to encode and process textual information. Much work has investigated how the conceptual content of words translates into g…