2 citations · 5 across the 23 of their papers we have counts for
13 papers · 1 filter
ReGRA: Residual-Gradient Adaptation for Complementary Low-Rank Fine-Tuning
Fanyao Li, Yuxi Liu, Xiaohao Liu +3
Low-rank adaptation (LoRA) enables parameter-efficient fine-tuning by learning low-rank weight updates. Increasing rank expands adaptation capacity, but does not guarantee that all…
BARQ: Balanced Codebook Refinement for Low-Bit LLM Quantization
Chenhang Cui, Xu Xie, Linrui Xu +4
As large language models (LLMs) grow in parameter count, model storage and parameter memory traffic have become major bottlenecks to efficient deployment. Codebook-based weight qua…
DV-Lens: Revealing the Functional Organization of Language Model Parameters
Chenhang Cui, Jian Yu, Shuyi Miao +5
Understanding parameter functions helps elucidate the internal mechanisms of large language models (LLMs). However, how to connect parameters from different modules to verifiable o…
Beyond Cross-Lingual Transfer: Benchmarking Propagation Boundaries in Multilingual LLM Unlearning
Pengyang Shao, Chuanpeng Lu, Wei Qin +5
Large Language Model (LLM) unlearning aims to suppress target knowledge while preserving general capabilities. In multilingual settings, unlearning must additionally propagate with…
Hyperbolic Multimodal Continual Learning
Jiahong Liu, Ming Shen, Xiaohao Liu +4
Hyperbolic geometry has recently emerged as a powerful representation space for multimodal learning, as it naturally captures hierarchical semantic structure across modalities. Des…
CaIRec: Calibrated Modality Imputation for Incomplete Multimodal Recommendation
Ruiyu Liu, Xiaohao Liu, Miaomiao Cai +2
Real-world multimodal recommender systems often face incomplete modality observations, where items lack images, text, or other content features. Such incompleteness weakens item re…
CoLAS: Multimodal Corroboration of Latent Asset Signals for Financial Trading
Yanzheng Jin, Pengyang Shao, Xiaohao Liu +3
Financial trading relies on extracting reliable signals from heterogeneous market modalities such as price series, breaking news, and investor sentiment. Existing multimodal method…
Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment
Haoyuan Wang, Xiaohao Liu, Jiajie Su +2
Multimodal large language models (MLLMs) need efficient mechanisms to update knowledge without degrading existing capabilities. While intrinsic multimodal knowledge editing achieve…
QuantClaw: Precision Where It Matters for OpenClaw
Manyi Zhang, Ji-Fu Li, Zhongao Sun +5
Autonomous agent systems such as OpenClaw introduce significant efficiency challenges due to long-context inputs and multi-turn reasoning. This results in prohibitively high comput…
Omnimodal Dataset Distillation via High-order Proxy Alignment
Yuxuan Gao, Xiaohao Liu, Xiaobo Xia +1
Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving training performance, but existing methods are largely restricted to single-modal…
FreeAct: Freeing Activations for LLM Quantization
Xiaohao Liu, Xiaobo Xia, Manyi Zhang +6
Quantization is pivotal for mitigating the significant memory and computational overhead of Large Language Models (LLMs). While emerging transformation-based methods have successfu…
MusicSem: A Semantically Rich Language--Audio Dataset of Natural Music Descriptions
Rebecca Salganik, Teng Tu, Fei-Yueh Chen +8
Music representation learning is central to music information retrieval and generation. While recent advances in multimodal learning have improved alignment between text and audio…
Align Once, Benefit Multilingually: Enforcing Multilingual Consistency for LLM Safety Alignment
Yuyan Bu, Xiaohao Liu, ZhaoXing Ren +2
The widespread deployment of large language models (LLMs) across linguistic communities necessitates reliable multilingual safety alignment. However, recent efforts to extend align…