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From the 2 of 73 linked papers with an AI index.

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20242026
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cs.CL2026

Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models

Yusuf Sahin, Ahmed Rockey Saikia, Volkan Cevher +1

The paper proposes ADAS, a training‑free attention‑discounted reranking rule that improves parallel masked diffusion decoding by penalizing tokens that strongly attend to uncertain…

cs.CL2026

Selective Rotary Position Embedding

Sajad Movahedi, Timur Carstensen, Arshia Afzal +3

Position information is essential for language modeling. In softmax transformers, Rotary Position Embeddings (\textit{RoPE}) encode positions through \textit{fixed-angle} rotations…

cs.CL2025

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning

Yixin Wan, Anil Ramakrishna, Kai-Wei Chang +2

Large Language Model (LLM) unlearning has recently gained significant attention, driven by the need to remove unwanted information, such as private, sensitive, or copyrighted conte…

cs.CL2025

SemEval-2025 Task 4: Unlearning sensitive content from Large Language Models

Anil Ramakrishna, Yixin Wan, Xiaomeng Jin +6

We introduce SemEval-2025 Task 4: unlearning sensitive content from Large Language Models (LLMs). The task features 3 subtasks for LLM unlearning spanning different use cases: (1)…

cs.CL2025

LUME: LLM Unlearning with Multitask Evaluations

Anil Ramakrishna, Yixin Wan, Xiaomeng Jin +6

Unlearning aims to remove copyrighted, sensitive, or private content from large language models (LLMs) without a full retraining. In this work, we develop a multi-task unlearning b…

cs.CL2024

Extreme Miscalibration and the Illusion of Adversarial Robustness

Vyas Raina, Samson Tan, Volkan Cevher +3

Deep learning-based Natural Language Processing (NLP) models are vulnerable to adversarial attacks, where small perturbations can cause a model to misclassify. Adversarial Training…