activity
20242026
most citedA Survey of Resource-efficient LLM and Multimodal Foundation Models

32 citations · 32 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Beyond Imitation: Filtering On-Policy Distillation by Reasoning Progress

Chen Yang, Haiyuan Wan, Rengrong Xiong +2

On-policy distillation (OPD) has emerged as an effective framework for post-training language models by pairing student-generated trajectories with dense token-level supervision fr…

cs.CR2025

Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing

Jinhua Yin, Peiru Yang, Chen Yang +5

Large vision-language models (LVLMs) derive their capabilities from extensive training on vast corpora of visual and textual data. Empowered by large-scale parameters, these models…

cs.CL2025

RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model Merging

Bowen Wang, Haiyuan Wan, Liwen Shi +10

We unveil that internal representations in large language models (LLMs) serve as reliable proxies of learned knowledge, and propose RECALL, a novel representation-aware model mergi…

cs.LG2025

RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations

Chang Xue, Youwei Lu, Chen Yang +1

Personalization is a core capability across consumer technologies, streaming, shopping, wearables, and voice, yet it remains challenged by sparse interactions, fast content churn,…

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…

cs.CL2024

The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis

Chen Yang, Junzhuo Li, Xinyao Niu +11

Uncovering early-stage metrics that reflect final model performance is one core principle for large-scale pretraining. The existing scaling law demonstrates the power-law correlati…

cs.LG2024★ 32 cited

A Survey of Resource-efficient LLM and Multimodal Foundation Models

Mengwei Xu, Wangsong Yin, Dongqi Cai +15

Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine lear…