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20242026
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cs.LG2026

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks

Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1

With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…

cs.LG2026

Breaking the Correlation Plateau: On the Optimization and Capacity Limits of Attention-Based Regressors

Jingquan Yan, Yuwei Miao, Peiran Yu +1

Attention-based regression models are often trained by jointly optimizing Mean Squared Error (MSE) loss and Pearson correlation coefficient (PCC) loss, emphasizing the magnitude of…

cs.LG2025

Provably Mitigating Corruption, Overoptimization, and Verbosity Simultaneously in Offline and Online RLHF/DPO Alignment

Ziyi Chen, Junyi Li, Peiran Yu +1

Reinforcement learning from human feedback (RLHF) and direct preference optimization (DPO) are important techniques to align large language models (LLM) with human preference. Howe…

cs.LG2025

Cost-Aware Contrastive Routing for LLMs

Reza Shirkavand, Shangqian Gao, Peiran Yu +1

We study cost-aware routing for large language models across diverse and dynamic pools of models. Existing approaches often overlook prompt-specific context, rely on expensive mode…

cs.LG2025

Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness

Qi He, Peiran Yu, Ziyi Chen +1

Shuffling-type gradient methods are favored in practice for their simplicity and rapid empirical performance. Despite extensive development of convergence guarantees under various…

cs.LG2025

Bilevel ZOFO: Efficient LLM Fine-Tuning and Meta-Training

Reza Shirkavand, Peiran Yu, Qi He +1

Fine-tuning pre-trained Large Language Models (LLMs) for downstream tasks using First-Order (FO) optimizers presents significant computational challenges. Parameter-Efficient Fine-…

cs.LG2024

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models

Reza Shirkavand, Peiran Yu, Shangqian Gao +3

Recent advances in diffusion generative models have yielded remarkable progress. While the quality of generated content continues to improve, these models have grown considerably i…