6 citations · 20 across the 25 of their papers we have counts for
29 papers
AlignPred: Error-Controlled KV Cache Compression via Alignment and Predictive Coding
Xu Yang, Jiapeng Zhang, Zhiwei Zuo +5
Long-running agents retain KV caches across turns and sessions for hours or days. Compressing these persistent caches requires reducing storage while controlling reconstruction err…
TQTS-Bench: A Multi-Syntax Benchmark for Text-to-Query over Time-Series Databases
Fei Lyu, Zhiyi Peng, Jiaming Liu +5
Large language models (LLMs) have significantly advanced natural language querying over relational databases, yet their ability to query time-series databases (TSDBs) remains large…
RayLift: Lifting Complementary Ray-Wise Evidence with 3D Geometry Priors for Semantic Scene Completion
Meng Wang, Hongxia Yu, Wenzhe He +4
Camera-based 3D semantic scene completion (SSC) provides comprehensive scene understanding for autonomous driving and robotics. However, existing methods often treat stereo depth e…
Exponential Separation of Quantum and Classical One-Way Numbers-on-Forehead Communication
Guangxu Yang, Jiapeng Zhang
Numbers-on-Forehead (NOF) communication model is a central model in communication complexity. As a restricted variant, one-way NOF model is of particular interest. Establishing str…
Self-Indexing KVCache: Predicting Sparse Attention from Compressed Keys
Xu Yang, Jiapeng Zhang, Dongyang Zhao +2
The KV cache in self-attention has emerged as a major bottleneck in long-context and large-batch inference for LLMs. Existing approaches often treat sparsity prediction and compres…
LiNeXt: Revisiting LiDAR Completion with Efficient Non-Diffusion Architectures
Wenzhe He, Xiaojun Chen, Ruiqi Wang +5
3D LiDAR scene completion from point clouds is a fundamental component of perception systems in autonomous vehicles. Previous methods have predominantly employed diffusion models f…
Enhancing Small-Scale Dataset Expansion with Triplet-Connection-based Sample Re-Weighting
Ting Xiang, Changjian Chen, Zhuo Tang +5
The performance of computer vision models in certain real-world applications, such as medical diagnosis, is often limited by the scarcity of available images. Expanding datasets us…
CoreSPECT: Enhancing Clustering Algorithms via an Interplay of Density and Geometry
Chandra Sekhar Mukherjee, Joonyoung Bae, Jiapeng Zhang
In this paper, we provide a novel perspective on the underlying structure of real-world data with ground-truth clusters via characterization of an abundantly observed yet often ove…
Quantum versus Classical Separation in Simultaneous Number-on-Forehead Communication
Guangxu Yang, Jiapeng Zhang
Quantum versus classical separation plays a central role in understanding the advantages of quantum computation. In this paper, we present the first exponential separation between…
Deterministic Lifting Theorems for One-Way Number-on-Forehead Communication
Guangxu Yang, Jiapeng Zhang
Lifting theorems are one of the most powerful tools for proving communication lower bounds, with numerous downstream applications in proof complexity, monotone circuit lower bounds…
Gadgetless Lifting Beats Round Elimination: Improved Lower Bounds for Pointer Chasing
Xinyu Mao, Guangxu Yang, Jiapeng Zhang
We prove an Ω(n/k+k) communication lower bound on (k-1)-round distributional complexity of the k-step pointer chasing problem under uniform input distribution, improving the Ω(n/k…
A multi-core periphery perspective: Ranking via relative centrality
Chandra Sekhar Mukherjee, Jiapeng Zhang
Community and core-periphery are two widely studied graph structures, with their coexistence observed in real-world graphs (Rombach, Porter, Fowler \& Mucha [SIAM J. App. Math. 201…
FedMPQ: Secure and Communication-Efficient Federated Learning with Multi-codebook Product Quantization
Xu Yang, Jiapeng Zhang, Qifeng Zhang +1
In federated learning, particularly in cross-device scenarios, secure aggregation has recently gained popularity as it effectively defends against inference attacks by malicious ag…
A New Information Complexity Measure for Multi-pass Streaming with Applications
Mark Braverman, Sumegha Garg, Qian Li +3
We introduce a new notion of information complexity for multi-pass streaming problems and use it to resolve several important questions in data streams. In the coin problem, one se…
On the Power of SVD in the Stochastic Block Model
Xinyu Mao, Jiapeng Zhang
A popular heuristic method for improving clustering results is to apply dimensionality reduction before running clustering algorithms. It has been observed that spectral-based dime…
Lifting Theorems Meet Information Complexity: Known and New Lower Bounds of Set-disjointness
Guangxu Yang, Jiapeng Zhang
Set-disjointness problems are one of the most fundamental problems in communication complexity and have been extensively studied in past decades. Given its importance, many lower b…
Streaming Lower Bounds and Asymmetric Set-Disjointness
Shachar Lovett, Jiapeng Zhang
Frequency estimation in data streams is one of the classical problems in streaming algorithms. Following much research, there are now almost matching upper and lower bounds for the…
Detecting Hidden Communities by Power Iterations with Connections to Vanilla Spectral Algorithms
Chandra Sekhar Mukherjee, Jiapeng Zhang
Community detection in the stochastic block model is one of the central problems of graph clustering. Since its introduction, many subsequent papers have made great strides in solv…
Best-of-Both-Worlds Multiparty Quantum Computation with Publicly Verifiable Identifiable Abort
Kai-Min Chung, Mi-Ying Huang, Er-Cheng Tang +1
Alon et al. (CRYPTO 2021) introduced a multiparty quantum computation protocol that is secure with identifiable abort (MPQC-SWIA). However, their protocol allows only inside MPQC p…
Confident Clustering via PCA Compression Ratio and Its Application to Single-cell RNA-seq Analysis
Yingcong Li, Chandra Sekhar Mukherjee, Jiapeng Zhang
Unsupervised clustering algorithms for vectors has been widely used in the area of machine learning. Many applications, including the biological data we studied in this paper, cont…
Capturing the Denoising Effect of PCA via Compression Ratio
Chandra Sekhar Mukherjee, Nikhil Doerkar, Jiapeng Zhang
Principal component analysis (PCA) is one of the most fundamental tools in machine learning with broad use as a dimensionality reduction and denoising tool. In the later setting, w…
Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle
Chandra Sekhar Mukherjee, Pan Peng, Jiapeng Zhang
The stochastic block model (SBM) is a fundamental model for studying graph clustering or community detection in networks. It has received great attention in the last decade and the…
Towards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle
Pan Peng, Jiapeng Zhang
Motivated by applications in crowdsourced entity resolution in database, signed edge prediction in social networks and correlation clustering, Mazumdar and Saha [NIPS 2017] propose…
Decision list compression by mild random restrictions
Shachar Lovett, Kewen Wu, Jiapeng Zhang
A decision list is an ordered list of rules. Each rule is specified by a term, which is a conjunction of literals, and a value. Given an input, the output of a decision list is the…