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20242026
most citedImproving Semantic Understanding in Speech Language Models via Brain-tuning

4 citations · 8 across the 34 of their papers we have counts for

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14 papers · 1 filter

cs.AI2025

PricingLogic: Evaluating LLMs Reasoning on Complex Tourism Pricing Tasks

Yunuo Liu, Dawei Zhu, Zena Al-Khalili +5

We present PricingLogic, the first benchmark that probes whether Large Language Models(LLMs) can reliably automate tourism-related prices when multiple, overlapping fare rules appl…

cs.LG2025

Decoding Partial Differential Equations: Cross-Modal Adaptation of Decoder-only Models to PDEs

Paloma García-de-Herreros, Philipp Slusallek, Dietrich Klakow +1

While large language models are primarily used on natural language tasks, they have also shown great promise when adapted to new modalities, e.g., for scientific machine learning t…

cs.LG2025

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches

Israel Abebe Azime, Deborah D. Kanubala, Tejumade Afonja +4

Large Language Models (LLMs) are increasingly employed in high-stakes decision-making tasks, such as loan approvals. While their applications expand across domains, LLMs struggle t…

cs.CL2025

Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages

Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow +2

Large language models (LLMs) have demonstrated significant capabilities in solving mathematical problems expressed in natural language. However, multilingual and culturally-grounde…

cs.CL2025

Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMs

Elisa Forcada Rodríguez, Olatz Perez-de-Viñaspre, Jon Ander Campos +2

One of the goals of fairness research in NLP is to measure and mitigate stereotypical biases that are propagated by NLP systems. However, such work tends to focus on single axes of…

cs.AI2025

Implementing Rational Choice Functions with LLMs and Measuring their Alignment with User Preferences

Anna Karnysheva, Christian Drescher, Dietrich Klakow

As large language models (LLMs) become integral to intelligent user interfaces (IUIs), their role as decision-making agents raises critical concerns about alignment. Although exten…

cs.CL2025

Evaluating Intermediate Reasoning of Code-Assisted Large Language Models for Mathematics

Zena Al-Khalili, Nick Howell, Dietrich Klakow

Assisting LLMs with code generation improved their performance on mathematical reasoning tasks. However, the evaluation of code-assisted LLMs is generally restricted to execution c…

cs.CL2025

Agree to Disagree? A Meta-Evaluation of LLM Misgendering

Arjun Subramonian, Vagrant Gautam, Preethi Seshadri +3

Numerous methods have been proposed to measure LLM misgendering, including probability-based evaluations (e.g., automatically with templatic sentences) and generation-based evaluat…

cs.CL2025

Aligned Probing: Relating Toxic Behavior and Model Internals

Andreas Waldis, Vagrant Gautam, Anne Lauscher +2

We introduce aligned probing, a novel interpretability framework that aligns the behavior of language models (LMs), based on their outputs, and their internal representations (inte…

cs.CL2025

INJONGO: A Multicultural Intent Detection and Slot-filling Dataset for 16 African Languages

Hao Yu, Jesujoba O. Alabi, Andiswa Bukula +19

Slot-filling and intent detection are well-established tasks in Conversational AI. However, current large-scale benchmarks for these tasks often exclude evaluations of low-resource…

cs.CL2025

Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning

Xinghao Chen, Zhijing Sun, Wenjin Guo +8

Large Language Models (LLMs) excel in reasoning tasks through Chain-of-Thought (CoT) prompting. However, CoT prompting greatly increases computational demands, which has prompted g…

cs.CL2025★ 2 cited

Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding

Tadesse Destaw Belay, Israel Abebe Azime, Abinew Ali Ayele +5

Large Language Models (LLMs) show promising learning and reasoning abilities. Compared to other NLP tasks, multilingual and multi-label emotion evaluation tasks are under-explored…

cs.CL2025

AFRIDOC-MT: Document-level MT Corpus for African Languages

Jesujoba O. Alabi, Israel Abebe Azime, Miaoran Zhang +13

This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùbá, and Zulu. The da…

cs.LG2025

IGC: Integrating a Gated Calculator into an LLM to Solve Arithmetic Tasks Reliably and Efficiently

Florian Dietz, Dietrich Klakow

Solving arithmetic tasks is a simple and fundamental skill, yet modern Large Language Models (LLMs) have great difficulty with them. We introduce the Integrated Gated Calculator (I…