11 citations · 23 across the 21 of their papers we have counts for
36 papers · 1 filter
Uncertainty-Aware Generation and Decision-Making Under Ambiguity
Nico Daheim, Iryna Gurevych
With rapidly improving capabilities, Large Language Models (LLMs) are increasingly used in many complex real-world tasks. Beyond requiring in-depth knowledge and reasoning skills,…
Decision-Making with Deliberation: Meta-reviewing as a Document-grounded Dialogue
Sukannya Purkayastha, Nils Dycke, Anne Lauscher +1
Meta-reviewing is a pivotal stage in the peer-review process, serving as the final step in determining whether a paper is recommended for acceptance. Prior research on meta-reviewi…
From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
David Dinucu-Jianu, Jakub Macina, Nico Daheim +3
Large language models (LLMs) can transform education, but their optimization for direct question-answering often undermines effective pedagogy which requires strategically withhold…
LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews
Sukannya Purkayastha, Zhuang Li, Anne Lauscher +2
Peer review is a cornerstone of quality control in scientific publishing. With the increasing workload, the unintended use of `quick' heuristics, referred to as lazy thinking, has…
Token Weighting for Long-Range Language Modeling
Falko Helm, Nico Daheim, Iryna Gurevych
Many applications of large language models (LLMs) require long-context understanding, but models continue to struggle with such tasks. We hypothesize that conventional next-token p…
Uncertainty-Aware Decoding with Minimum Bayes Risk
Nico Daheim, Clara Meister, Thomas Möllenhoff +1
Despite their outstanding performance in the majority of scenarios, contemporary language models still occasionally generate undesirable outputs, for example, hallucinated text. Wh…