works on

From the 1 of 10 linked papers with an AI index.

activity
20242026
collaborators

10 papers

cs.AI2026

AIMO Interpretability Challenge

Michal Štefánik, Philipp Mondorf, Andreas Waldis +11

The paper introduces the AIMO Interpretability Challenge, a competition that evaluates whether advanced mathematical language models solve olympiad‑level problems using robust reas…

cs.CL2025

AfroBench: How Good are Large Language Models on African Languages?

Jessica Ojo, Odunayo Ogundepo, Akintunde Oladipo +4

Large-scale multilingual evaluations, such as MEGA, often include only a handful of African languages due to the scarcity of high-quality evaluation data and the limited discoverab…

cs.CL2025

TuBA: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning

Xuanli He, Jun Wang, Qiongkai Xu +4

The implications of backdoor attacks on English-centric large language models (LLMs) have been widely examined - such attacks can be achieved by embedding malicious behaviors durin…

cs.LG2025

How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective

Xinchi Qiu, William F. Shen, Yihong Chen +4

While unlearning knowledge from large language models (LLMs) is receiving increasing attention, one important aspect remains unexplored. Existing approaches and benchmarks assume d…

cs.CL2025

Multilingual Language Model Pretraining using Machine-translated Data

Jiayi Wang, Yao Lu, Maurice Weber +5

High-resource languages such as English, enables the pretraining of high-quality large language models (LLMs). The same can not be said for most other languages as LLMs still under…

cs.CL2025

Warmup Generations: A Task-Agnostic Approach for Guiding Sequence-to-Sequence Learning with Unsupervised Initial State Generation

Senyu Li, Zipeng Sun, Jiayi Wang +4

Traditional supervised fine-tuning (SFT) strategies for sequence-to-sequence tasks often train models to directly generate the target output. Recent work has shown that guiding mod…