7 citations · 13 across the 16 of their papers we have counts for
18 papers
Rent-Seeking Language Models: Reward Models Set the Prices, Frequent Audits Curb the Rent
Zixiao Wang, Xingbo Du, Duzhen Zhang +1
Reward model overoptimization in RLHF is usually described as reward hacking. We recast it as rent-seeking: the policy, a firm, earns reward from a regulator, the proxy reward mode…
ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB
Yifan Wu, Yuhan Li, Zhenhua Wang +6
Cloud-native serverless data warehouses achieve fine-grained elasticity by decoupling storage from compute, yet determining the optimal resource allocation for highly heterogeneous…
Guixu: Valuation-Driven Data Discovery for Autonomous AI Agents with On-Chain Attestation
Yifan Wu, Yuchen Peng, Jiaqi Chai +4
Autonomous agents increasingly rely on external data to complete downstream tasks such as model training and decision support. However, existing data discovery systems remain large…
Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects
Jun Zhang, Yicheng Ji, Feiyang Ren +7
Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency barrier known as visual token d…
Saliency-Guided Representation with Consistency Policy Learning for Visual Unsupervised Reinforcement Learning
Jingbo Sun, Qichao Zhang, Songjun Tu +5
Zero-shot unsupervised reinforcement learning (URL) offers a promising direction for building generalist agents capable of generalizing to unseen tasks without additional supervisi…
HybridKV: Hybrid KV Cache Compression for Efficient Multimodal Large Language Model Inference
Bowen Zeng, Feiyang Ren, Jun Zhang +4
Multimodal Large Language Models (MLLMs) have advanced unified reasoning over text, images, and videos, but their inference is hindered by the rapid growth of key-value (KV) caches…
SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search
Yuchen Peng, Dingyu Yang, Zhongle Xie +4
Approximate Nearest Neighbor Search (ANNS) underpins modern applications such as information retrieval and recommendation. With the rapid growth of vector data, efficient indexing…
SafeLoad: Efficient Admission Control Framework for Identifying Memory-Overloading Queries in Cloud Data Warehouses
Yifan Wu, Yuhan Li, Zhenhua Wang +8
Memory overload is a common form of resource exhaustion in cloud data warehouses. When database queries fail due to memory overload, it not only wastes critical resources such as C…
TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery
Lingxi Cui, Guanyu Jiang, Huan Li +3
The rise of LLM has enabled natural language-based table assistants, but existing systems assume users already have a well-formed table, neglecting the challenge of table discovery…
FloE: On-the-Fly MoE Inference on Memory-constrained GPU
Yuxin Zhou, Zheng Li, Jun Zhang +5
With the widespread adoption of Mixture-of-Experts (MoE) models, there is a growing demand for efficient inference on memory-constrained devices. While offloading expert parameters…
HMI: Hierarchical Knowledge Management for Efficient Multi-Tenant Inference in Pretrained Language Models
Jun Zhang, Jue Wang, Huan Li +6
The significant computational demands of pretrained language models (PLMs), which often require dedicated hardware, present a substantial challenge in serving them efficiently, esp…
NLCTables: A Dataset for Marrying Natural Language Conditions with Table Discovery
Lingxi Cui, Huan Li, Ke Chen +2
With the growing abundance of repositories containing tabular data, discovering relevant tables for in-depth analysis remains a challenging task. Existing table discovery methods p…
Preventing the Popular Item Embedding Based Attack in Federated Recommendations
Jun Zhang, Huan Li, Dazhong Rong +3
Privacy concerns have led to the rise of federated recommender systems (FRS), which can create personalized models across distributed clients. However, FRS is vulnerable to poisoni…
A Comprehensive Study of Shapley Value in Data Analytics
Hong Lin, Shixin Wan, Zhongle Xie +4
Over the recent years, Shapley value (SV), a solution concept from cooperative game theory, has found numerous applications in data analytics (DA). This paper presents the first co…
KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs
Yongqin Xu, Huan Li, Ke Chen +1
Schema matching (SM) and entity matching (EM) tasks are crucial for data integration. While large language models (LLMs) have shown promising results in these tasks, they suffer fr…
Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI
Lingxi Cui, Huan Li, Ke Chen +2
Machine learning (ML) on tabular data is ubiquitous, yet obtaining abundant high-quality tabular data for model training remains a significant obstacle. Numerous works have focused…
FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
Hong Lin, Lidan Shou, Ke Chen +2
Federated learning (FL) is a promising approach for learning a model from data distributed on massive clients without exposing data privacy. It works effectively in the ideal feder…
CARAT: Contrastive Feature Reconstruction and Aggregation for Multi-Modal Multi-Label Emotion Recognition
Cheng Peng, Ke Chen, Lidan Shou +1
Multi-modal multi-label emotion recognition (MMER) aims to identify relevant emotions from multiple modalities. The challenge of MMER is how to effectively capture discriminative f…