activity
20172026
most citedMCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge

68 citations · 84 across the 51 of their papers we have counts for

collaborators

55 papers

cs.CL2026

From Concept Alignment to Causal Grounding: An Intervention Test of Chain-of-Thought Faithfulness

Qianli Wang, Yilong Wang, Dennis Wei +5

Chain-of-thought (CoT) can sound plausible yet be unfaithful to the model's underlying reasoning. Most prior work probes CoT faithfulness through input--output behavior or input at…

cs.CL2026

FineWeb-CLaR: Culture, Language, and Region Annotations for Benchmark-Aligned Corpus Auditing

Yusser Al Ghussin, Eva Gavaller, Cristina España-Bonet +2

Cultural evaluation coverage and robustness in language models are difficult to diagnose because pretraining corpora and cultural benchmarks are rarely indexed with comparable meta…

cs.CL2026

Limitations of Automated Simulatability: LLM Simulators Can Bypass Explanations

Antonin Poché, Fanny Jourdan, Nils Feldhus +6

Simulatability is an evaluation protocol for explanations that quantifies their usefulness by how well they help a user predict a task model's outputs. Since human evaluation is co…

cs.CL2026

Compositional Multilingual and Behavioral Attribute Steering

Hyun Gu Kang, Daniil Gurgurov, Tanja Baeumel +2

This study examines the compositionality of steering vectors for language and behavioral control in large language models. Focusing on language, jailbreak, and conciseness, we inve…

cs.CL2026

When Tokenization is Secretly Output Supervision

Tanja Baeumel, Josef van Genabith, Simon Ostermann

Tokenization in language models is treated by default as an input preprocessing decision. We argue that this framing is incomplete: in autoregressive models, tokenizer granularity…

cs.CL2026

Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs

Mikhail Sonkin, Tanja Baeumel, Daniil Gurgurov +2

Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from o…