papers

Publications (41)

cs.LG2025

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory

Zhi Zhang, Chris Chow, Yasi Zhang +7

Lifelong reinforcement learning (RL) has been developed as a paradigm for extending single-task RL to more realistic, dynamic settings. In lifelong RL, the "life" of an RL agent is…

stat.ML2026

Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning

Haochen Zhang, Zhong Zheng, Lingzhou Xue

Motivated by real-world settings where data collection and policy deployment -- whether for a single agent or across multiple agents -- are costly, we study the problem of on-polic…

cs.CL2026

Revisiting Observation Reduction for Web Agents: Comprehensive Evaluation with a Lightweight Framework

Masafumi Enomoto, Ryoma Obara, Haochen Zhang +1

HTML observations in LLM-based web agents are extremely long, and while many reduction methods have been proposed, it remains unclear which methods reduce overall agent latency whi…

stat.ML2025

Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition

Zhong Zheng, Haochen Zhang, Lingzhou Xue

We study the gap-dependent bounds of two important algorithms for on-policy Q-learning for finite-horizon episodic tabular Markov Decision Processes (MDPs): UCB-Advantage (Zhang et…

cs.RO2024

VLA-3D: A Dataset for 3D Semantic Scene Understanding and Navigation

Haochen Zhang, Nader Zantout, Pujith Kachana +3

With the recent rise of Large Language Models (LLMs), Vision-Language Models (VLMs), and other general foundation models, there is growing potential for multimodal, multi-task embo…

eess.IV2024

Computational Pathology: A Survey Review and The Way Forward

Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc-Huy Trinh +18

Computational Pathology CPath is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main ob…

cs.IR2025

CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems

Haochen Zhang, Tianyi Zhang, Junze Yin +3

Recommender systems play a pivotal role in providing relevant content to users. With the rapid development of large language models (LLMs), researchers have begun utilizing LLMs to…

cs.IT2019

On The Classification-Distortion-Perception Tradeoff

Dong Liu, Haochen Zhang, Zhiwei Xiong

Signal degradation is ubiquitous and computational restoration of degraded signal has been investigated for many years. Recently, it is reported that the capability of signal resto…

cs.AI2024

Jellyfish: A Large Language Model for Data Preprocessing

Haochen Zhang, Yuyang Dong, Chuan Xiao +1

This paper explores the utilization of LLMs for data preprocessing (DP), a crucial step in the data mining pipeline that transforms raw data into a clean format conducive to easy p…

cs.DB2026

SQL-RewriteBench: A Correctness-Gated, Full-Denominator Benchmark for Statement-Level SQL Rewriting [Experiment,Analysis & Benchmark]

Jiang Long, Tianci Gao, Shiyuan Hao +3

Statement-level SQL rewriting can improve query performance and maintainability without changing the DBMS kernel, but existing benchmarks do not evaluate rewrite methods as deploya…

cs.RO2026

FAST-EQA: Efficient Embodied Question Answering with Global and Local Region Relevancy

Haochen Zhang, Nirav Savaliya, Faizan Siddiqui +1

Embodied Question Answering (EQA) combines visual scene understanding, goal-directed exploration, spatial and temporal reasoning under partial observability. A central challenge is…

stat.ML2025

Gap-Dependent Bounds for Federated -learning

Haochen Zhang, Zhong Zheng, Lingzhou Xue

We present the first gap-dependent analysis of regret and communication cost for on-policy federated -Learning in tabular episodic finite-horizon Markov decision processes (MDPs…

cs.AI2026

cotomi Act: Learning to Automate Work by Watching You

Masafumi Oyamada, Kunihiro Takeoka, Kosuke Akimoto +5

What if a browser agent could learn your work simply by watching you do it? We present cotomi Act, a browser-based computer-using agent that combines reliable multi-step task execu…

stat.ML2026

Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation

Haochen Zhang, Zhong Zheng, Lingzhou Xue

We study gap-dependent performance guarantees for nearly minimax-optimal algorithms in reinforcement learning with linear function approximation. While prior works have established…

cond-mat.str-el2023

Ultrafast spin dynamics in the proximate quantum spin liquid α-RuCl3

Haochen Zhang, Subin Kim, Young-June Kim +2

α-RuCl3 is a Kitaev material suggested to be a proximate quantum spin liquid in a certain temperature and magnetic field range. Nonequilibrium measurements of transient dynamics h…

hep-th2024

CFT from TQFT via Holographic Tensor Network, and Precision Discretisation of CFT

Lin Chen, Haochen Zhang, Kaixin Ji +4

We show that the path-integral of conformal field theories in dimensions (CFT) can be constructed by solving for eigenstates of an RG operator following from the Turaev-Vir…

cs.CV2020

Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?

Haochen Zhang, Dong Liu, Zhiwei Xiong

Recent advances of deep learning lead to great success of image and video super-resolution (SR) methods that are based on convolutional neural networks (CNN). For video SR, advance…

cs.LG2026

Support Basis: Fast Attention Beyond Bounded Entries

Maryam Aliakbarpour, Vladimir Braverman, Junze Yin +1

Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks. However, the quadratic complexity of softmax attention remains a central bottlen…

cond-mat.mtrl-sci2023

Revealing unusual bandgap shifts with temperature and bandgap renormalization effect in phase-stabilized metal halide perovskite thin films

Haochen Zhang, Zhixuan Bi, Zehua Zhai +11

Hybrid organic-inorganic metal halide perovskites are emerging materials in photovoltaics, whose bandgap is one of the most crucial parameters governing their light harvesting perf…

cs.LG2025

Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining

Haochen Zhang, Junze Yin, Guanchu Wang +5

Low-rank optimization has emerged as a promising approach to enabling memory-efficient training of large language models (LLMs). Existing low-rank optimization methods typically pr…

eess.SY2022

Resilient Distribution System Restoration with Communication Recovery by Drone Small Cells

Haochen Zhang, Chen Chen, Shunbo Lei +1

Distribution system (DS) restoration after natural disasters often faces the challenge of communication failures to feeder automation (FA) facilities, resulting in prolonged load p…

cond-mat.mes-hall2025

High-Precision Temperature Estimation Based on Magnetic Nanoparticles Dominated by Brownian Relaxation under Combined AC and DC Magnetic Fields

Zhongzhou Du, Wenze Zhang, Yi Sun +10

Brownian relaxation is one of the primary mechanisms that allows magnetic nanoparticles (MNPs) to convert magnetic energy into thermal energy under an excitation magnetic field. Ac…

cs.AI2024

Large Language Models as Data Preprocessors

Haochen Zhang, Yuyang Dong, Chuan Xiao +1

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of…

stat.ML2026

Q-Learning with Fine-Grained Gap-Dependent Regret

Haochen Zhang, Zhong Zheng, Lingzhou Xue

We study fine-grained gap-dependent regret bounds for model-free reinforcement learning in episodic tabular Markov Decision Processes. Existing model-free algorithms achieve minima…

stat.ML2025

Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost

Zhong Zheng, Haochen Zhang, Lingzhou Xue

In this paper, we consider model-free federated reinforcement learning for tabular episodic Markov decision processes. Under the coordination of a central server, multiple agents c…

cs.CV2025

Topology-Preserving Image Segmentation with Spatial-Aware Persistent Feature Matching

Bo Wen, Haochen Zhang, Dirk-Uwe G. Bartsch +3

Topological correctness is critical for segmentation of tubular structures, which pervade in biomedical images. Existing topological segmentation loss functions are primarily based…

cs.LG2026

Legendre Memory Unit with A Multi-Slice Compensation Model for Short-Term Wind Speed Forecasting Based on Wind Farm Cluster Data

Mumin Zhang, Haochen Zhang, Xin Zhi Khoo +4

With more wind farms clustered for integration, the short-term wind speed prediction of such wind farm clusters is critical for normal operation of power systems. This paper focuse…

cond-mat.mtrl-sci2025

Intrinsic exciton transport and recombination in single-crystal lead bromide perovskite

Zhixuan Bi, Yunfei Bai, Ying Shi +13

Photogenerated carrier transport and recombination in metal halide perovskites are critical to device performance. Despite considerable efforts, sample quality issues and measureme…

cs.AI2023

Adaptive Liquidity Provision in Uniswap V3 with Deep Reinforcement Learning

Haochen Zhang, Xi Chen, Lin F. Yang

Decentralized exchanges (DEXs) are a cornerstone of decentralized finance (DeFi), allowing users to trade cryptocurrencies without the need for third-party authorization. Investors…

cs.LG2026

Zero-Shot Transfer Capabilities of the Sundial Foundation Model for Leaf Area Index Forecasting

Peining Zhang, Hongchen Qin, Haochen Zhang +3

This work investigates the zero-shot forecasting capability of time series foundation models for Leaf Area Index (LAI) forecasting in agricultural monitoring. Using the HiQ dataset…

cs.CV2025

SORT3D: Spatial Object-centric Reasoning Toolbox for Zero-Shot 3D Grounding Using Large Language Models

Nader Zantout, Haochen Zhang, Pujith Kachana +4

Interpreting object-referential language and grounding objects in 3D with spatial relations and attributes is essential for robots operating alongside humans. However, this task is…

cs.LG2021

Learning by Passing Tests, with Application to Neural Architecture Search

Xuefeng Du, Haochen Zhang, Pengtao Xie

Learning through tests is a broadly used methodology in human learning and shows great effectiveness in improving learning outcome: a sequence of tests are made with increasing lev…

cs.RO2026

Flatness Preserves Instruction Following in Vision-Language-Action Models

Haochen Zhang, Yonatan Bisk

Vision-language-action (VLA) models have the potential for open-world generalization by leveraging pretrained vision-language representations, yet downstream finetuning on limited…

cs.CV2025

IRef-VLA: A Benchmark for Interactive Referential Grounding with Imperfect Language in 3D Scenes

Haochen Zhang, Nader Zantout, Pujith Kachana +2

With the recent rise of large language models, vision-language models, and other general foundation models, there is growing potential for multimodal, multi-task robotics that can…

cs.CV2019

Two-Stream Action Recognition-Oriented Video Super-Resolution

Haochen Zhang, Dong Liu, Zhiwei Xiong

We study the video super-resolution (SR) problem for facilitating video analytics tasks, e.g. action recognition, instead of for visual quality. The popular action recognition meth…

cs.CV2026

Non-Markov Multi-Round Conversational Image Generation with History-Conditioned MLLMs

Haochen Zhang, Animesh Sinha, Felix Juefei-Xu +8

Conversational image generation requires a model to follow user instructions across multiple rounds of interaction, grounded in interleaved text and images that accumulate as chat…

cond-mat.mtrl-sci2023

Spin Coherence and Spin Relaxation in Hybrid Organic-Inorganic Lead and Mixed Lead-Tin Perovskites

Haochen Zhang, Zehua Zhai, Zhixuan Bi +5

Metal halide perovskites make up a promising class of materials for semiconductor spintronics. Here we report a systematic investigation of coherent spin precession, spin dephasing…

physics.med-ph2023

A Novel Estimation Method for Temperature of Magnetic Nanoparticles Dominated by Brownian Relaxation Based on Magnetic Particle Spectroscopy

Zhongzhou Du, Gaoli Zhao, Zhanpeng Hua +9

This paper presents a novel method for estimating the temperature of magnetic nanoparticles (MNPs) based on AC magnetization harmonics of MNPs dominated by Brownian relaxation. The…

physics.app-ph2022

Characterization of GaN-based HEMTs Down to 4.2 K for Cryogenic Applications

Bolun Zeng, Haochen Zhang, Zikun Xiang +9

The cryogenic performance of GaN-based HEMTs (high-electron-mobility transistors) is systematically investigated by the direct current (DC) and low-frequency noise (LFN) characteri…

cs.CL2026

Read More, Think More: Revisiting Observation Reduction for Web Agents

Masafumi Enomoto, Ryoma Obara, Haochen Zhang +1

Web agents based on large language models (LLMs) rely on observations of web pages -- commonly represented as HTML -- as the basis for identifying available actions and planning su…

cs.RO2026

Inductive Generalization for Robotic Manipulation

Annabella Macaluso, Haochen Zhang, Ishaan Masilamony +2

Understanding the generalization capabilities of visuomotor policies is essential in the development of capable robotic agents. Generalizable models learn structures that transfer…