3 citations · 8 across the 30 of their papers we have counts for
35 papers · 1 filter
Reinforcement Learning Can Amplify Emergent Misalignment from Harmless Rewards
Magnus Jørgenvåg, David Kaczér, Lasse Ruttert +3
Emergent misalignment (EM) is the surprising tendency of language models to become broadly misaligned after fine-tuning on narrowly misaligned examples. While EM has been extensive…
Can LLM Agents Identify Spoken Dialects like a Linguist?
Tobias Bystrich, Lukas Hamm, Maria Hassan +3
Due to the scarcity of labeled dialectal speech, audio dialect classification is a challenging task for most languages, including Swiss German. In this work, we explore the ability…
Conspiracy Frame: a Semiotically-Driven Approach for Conspiracy Theories Detection
Heidi Campana Piva, Shaina Ashraf, Maziar Kianimoghadam Jouneghani +4
Conspiracy theories are anti-authoritarian narratives that lead to social conflict, impacting how people perceive political information. To help in understanding this issue, we int…
Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
Mohammad H. A. Monfared, Lucie Flek, Akbar Karimi
We propose an agentic data augmentation method for Aspect-Based Sentiment Analysis (ABSA) that uses iterative generation and verification to produce high quality synthetic training…
PERSPECTRA: A Scalable and Configurable Pluralist Benchmark of Perspectives from Arguments
Shangrui Nie, Kian Omoomi, Lucie Flek +2
Pluralism, the capacity to engage with diverse perspectives without collapsing them into a single viewpoint, is critical for developing large language models that faithfully reflec…
Encoder Fine-tuning with Stochastic Sampling Outperforms Open-weight GPT in Astronomy Knowledge Extraction
Shivam Rawat, Lucie Flek, Akbar Karimi
Scientific literature in astronomy is rapidly expanding, making it increasingly important to automate the extraction of key entities and contextual information from research papers…