16 citations · 40 across the 17 of their papers we have counts for
3 papers · 1 filter
Rewarding Efficient Reasoning Improves Abstention on Underspecified Tasks in Reasoning Models
Polina Tsvilodub, Max Höth, Michael Franke +2
While modern large reasoning models (LRMs) excel at providing correct answers in many tasks, we provide additional evidence that they often struggle with a critical capability: kno…
Soft-Prompt Tuning for Fair and Efficient LLM Benchmark Evaluation
Selen Erkan, Bastian Boll, Kristian Kersting +2
Benchmark scores often misrepresent a large language model's (LLM's) knowledge, because they rely, e.g., on the model's ability to follow specific formatting requirements. This esp…
AtManRL: Towards Faithful Reasoning via Differentiable Attention Saliency
Max Henning Höth, Kristian Kersting, Björn Deiseroth +1
Large language models (LLMs) increasingly rely on chain-of-thought (CoT) reasoning to solve complex tasks. Yet ensuring that the reasoning trace both contributes to and faithfully…