2 citations · 5 across the 23 of their papers we have counts for
27 papers
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…
Calibrated Multimodal Representation Learning with Missing Modalities
Xiaohao Liu, Xiaobo Xia, Jiaheng Wei +4
Multimodal representation learning harmonizes distinct modalities by aligning them into a unified latent space. Recent research generalizes traditional cross-modal alignment to pro…
AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS
Hai Ling, Tianchi Wang, Xiaohao Liu +3
Modern Visual-Aware Recommender Systems (VARS) exploit the integration of user interaction data and visual features to deliver personalized recommendations with high precision. How…
Principled Multimodal Representation Learning
Xiaohao Liu, Xiaobo Xia, See-Kiong Ng +1
Multimodal representation learning seeks to create a unified representation space by integrating diverse data modalities to improve multimodal understanding. Traditional methods of…
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Yingzhi He, Xiaohao Liu, An Zhang +2
Sequential recommendation aims to predict users' future interactions by modeling collaborative filtering (CF) signals from historical behaviors of similar users or items. Tradition…
AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint
Leheng Sheng, Changshuo Shen, Weixiang Zhao +6
As LLMs are increasingly deployed in real-world applications, ensuring their ability to refuse malicious prompts, especially jailbreak attacks, is essential for safe and reliable u…
L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models
Xiaohao Liu, Xiaobo Xia, Weixiang Zhao +6
Large language models (LLMs) have achieved notable progress. Despite their success, next-token prediction (NTP), the dominant method for LLM training and inference, is constrained…
Extending Visual Dynamics for Video-to-Music Generation
Xiaohao Liu, Teng Tu, Yunshan Ma +1
Music profoundly enhances video production by improving quality, engagement, and emotional resonance, sparking growing interest in video-to-music generation. Despite recent advance…
Continual Multimodal Contrastive Learning
Xiaohao Liu, Xiaobo Xia, See-Kiong Ng +1
Multimodal Contrastive Learning (MCL) advances in aligning different modalities and generating multimodal representations in a joint space. By leveraging contrastive learning acros…
Towards Modality Generalization: A Benchmark and Prospective Analysis
Xiaohao Liu, Xiaobo Xia, Zhuo Huang +2
Multi-modal learning has achieved remarkable success by integrating information from various modalities, achieving superior performance in tasks like recognition and retrieval comp…
Headache to Overstock? Promoting Long-tail Items through Debiased Product Bundling
Shuo Xu, Haokai Ma, Yunshan Ma +4
Product bundling aims to organize a set of thematically related items into a combined bundle for shipment facilitation and item promotion. To increase the exposure of fresh or over…
Fine-tuning Multimodal Large Language Models for Product Bundling
Xiaohao Liu, Jie Wu, Zhulin Tao +3
Recent advances in product bundling have leveraged multimodal information through sophisticated encoders, but remain constrained by limited semantic understanding and a narrow scop…