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Showing 710 results for "hua qi" in Computer Science
Computer Science Preprint PDF DOI

Hu\'i S\`u: Co-constructing a Dual Feedback Apparatus

Yichen Wang, Charles Patrick Martin ยท 2026

This performance presents a duet between two intelligent musical instruments, S\`u (to trace back; to go upstream) and Agentier (playing on agentic clavier), and their human performers, connected throโ€ฆ

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Modeling Behavioral Intensity and Transitions for Generative Recommendation

Wenxuan Yang, Xiaoyang Xu, Hanyu Zhang, Zhexuan Xu, Wanqiang Xiong, Zhaoqun Chen ยท 2026

Multi-behavior recommendation aims to predict user conversions by modeling various interaction types that carry distinct intent signals. Recently, generative sequence modeling methods have emerged as โ€ฆ

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Exact, Efficient, and Reliable Multi-Objective and Multi-Constrained IoT Workflow Scheduling in Edge-Hub-Cloud Cyber-Physical Systems

Andreas Kouloumpris, Georgios L. Stavrinides, Maria K. Michael, Theocharis Theocharides ยท 2026

Emerging IoT-enabled cyber-physical applications demand low-latency, energy-efficient, and reliable execution across resource-constrained edge devices with heterogeneous multicore processors and diverโ€ฆ

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Computer Science Preprint PDF DOI

A Theory of Hanoi Omega-Automata and Games

Emmanuel Filiot, Allen Joseph, Guillermo A. Perez, Saina Sunny ยท 2026

The Hanoi Omega-Automata (HOA) format has established itself as the definitive standard for encoding $\omega$-regular automata in modern synthesis tools. While HOA is widely adopted due to its succincโ€ฆ

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SEMA-SQL: Beyond Traditional Relational Querying with Large Language Models

Yin Lin, Tianjing Zeng, Zhongjun Ding, Rong Zhu, Bolin Ding, H. V. Jagadish, Jingren Zhou ยท 2026

Relational databases excel at structured data analysis, but real-world queries increasingly require capabilities beyond standard SQL, such as semantically matching entities across inconsistent names, โ€ฆ

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Efficient Page Migration in Hybrid Memory Systems

Upasna, Venkata Kalyan Tavva ยท 2026

Heterogeneous Memory Architecture (HMA) aims to optimize memory usage by leveraging a combination of memory types, such as high-bandwidth memory (HBM), commodity DRAM, and non-volatile memory (NVM), wโ€ฆ

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Predictive Autoscaling for Node.js on Kubernetes: Lower Latency, Right-Sized Capacity

Ivan Tymoshenko, Luca Maraschi, Matteo Collina ยท 2026

Kubernetes offers two default paths for scaling Node\.js workloads, and both have structural limitations. The Horizontal Pod Autoscaler scales on CPU utilization, which does not directly measure eventโ€ฆ

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TensorHub: Rethinking AI Model Hub with Tensor-Centric Compression

Tingfeng Lan, Zirui Wang, Yunjia Zheng, Zhaoyuan Su, Juncheng Yang, Yue Cheng ยท 2026

Modern AI models are growing rapidly in size and redundancy, leading to significant storage and distribution challenges in model hubs. We present TensorHub, a tensor-centric system for reducing storagโ€ฆ

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Wave-Based Dispatch for Circuit Cutting in Hybrid HPC--Quantum Systems

Ricard S. Garcia-Raigada, Josep Jorba, Sergio Iserte ยท 2026

Hybrid High-performance Computing (HPC)-quantum workloads based on circuit cutting decompose large quantum circuits into independent fragments, but existing frameworks tightly couple cutting logic to โ€ฆ

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VeriGraphi: A Multi-Agent Framework of Hierarchical RTL Generation for Large Hardware Designs

Sazzadul Islam, Tasnim Tabassum, Hao Zheng ยท 2026

Generating synthesizable Verilog for large, hierarchical hardware designs remains a significant challenge for large language models (LLMs), which struggle to replicate the structured reasoning that huโ€ฆ

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HadAgent: Harness-Aware Decentralized Agentic AI Serving with Proof-of-Inference Blockchain Consensus

Landy Jimenez, Mariah Weatherspoon, Bingyu Shen, Yi Sheng, Jianming Liu, Boyang Li ยท 2026

Proof-of-Work (PoW) blockchain consensus consumes vast computational resources without producing useful output, while the rapid growth of large language model (LLM) agents has created unprecedented deโ€ฆ

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EPAC: The Last Dance

Filippo Mantovani, Fabio Banchelli, Pablo Vizcaino, Roger Ferrer, Oscar Palomar, Francesco Minervini, Jesus Labarta, Mauro Olivieri, Sebastiano Pomata, Pedro Marcuello, Jordi Cortina, Alberto Moreno, Josep Sans, Roger Espasa, Vassilis Papaefstathiou, Nikolaos Dimou, Georgios Ieronymakis, Antonis Psathakis, Michalis Giaourtas, Iasonas Mastorakis, Manolis Marazakis, Eric Guthmuller, Andrea Bocco, Jerome Fereyre, Cesar Fuguet, Mate Kovac, Mario Kovac, Luka Mrkovic, Josip Ramljak, Luca Bertaccini, Tim Fischer, Frank K. Gurkaynak, Paul Scheffler, Luca Benini, Bhavishya Goel, Madhavan Manivannan, Tiago Rocha, Nuno Neves, Jens Kruger ยท 2026

This paper presents EPAC, a RISC-V-based accelerator chip developed within the European Processor Initiative (EPI) as part of a multi-year, multi-partner effort to build a European HPC processor ecosyโ€ฆ

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L-PCN: A Point Cloud Accelerator Exploiting Spatial Locality through Octree-based Islandization

Yiming Gao, Jieming Yin, Yuxiang Wang, Xiangru Chen, Zhilei Chai, Bowen Jiang, Jiliang Zhang, Herman Lam ยท 2026

Existing Point Cloud Networks (PCNs) have proven to achieve great success in many point cloud tasks such as object part segmentation, shape classification, and so on. The most popular point-based PCNsโ€ฆ

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LLM-Rosetta: A Hub-and-Spoke Intermediate Representation for Cross-Provider LLM API Translation

Peng Ding ยท 2026

The rapid proliferation of Large Language Model (LLM) providers--each exposing proprietary API formats--has created a fragmented ecosystem where applications become tightly coupled to individual vendoโ€ฆ

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An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face

Yujian Liu, Xiao Yu, Jacky Keung, Xing Hu, Xin Xia, Xiaoxue Ma ยท 2026

Large language models (LLMs) have rapidly evolved from general-purpose systems to multimodal models capable of processing text, images, and audio. As both general-purpose LLMs (GLLMs) and multimodal Lโ€ฆ

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CareGuardAI: Context-Aware Multi-Agent Guardrails for Clinical Safety & Hallucination Mitigation in Patient-Facing LLMs

Elham Nasarian, Abhilash Neog, Kwok-Leung Tsui, Niyousha HosseiniChimeh ยท 2026

Integrating large language models (LLMs) into patient-facing healthcare systems offers significant potential to improve access to medical information. However, ensuring clinical safety and factual relโ€ฆ

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Comparing Human Oversight Strategies for Computer-Use Agents

Chaoran Chen, Zhiping Zhang, Zeya Chen, Eryue Xu, Yinuo Yang, Ibrahim Khalilov, Simret A Gebreegziabher, Yanfang Ye, Ziang Xiao, Yaxing Yao, Tianshi Li, Toby Jia-Jun Li ยท 2026

LLM-powered computer-use agents (CUAs) are shifting users from direct manipulation to supervisory coordination. Existing oversight mechanisms, however, have largely been studied as isolated interface โ€ฆ

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The Art of Building Verifiers for Computer Use Agents

Corby Rosset, Pratyusha Sharma, Andrew Zhao, Miguel Gonzalez-Fernandez, Ahmed Awadallah ยท 2026

Verifying the success of computer use agent (CUA) trajectories is a critical challenge: without reliable verification, neither evaluation nor training signal can be trusted. In this paper, we present โ€ฆ

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Attesting LLM Pipelines: Enforcing Verifiable Training and Release Claims

Zhuoran Tan, Jeremy Singer, Christos Anagnostopoulos ยท 2026

Modern Large Language Model (LLM) systems are assembled from third-party artifacts such as pre-trained weights, fine-tuning adapters, datasets, dependency packages, and container images, fetched throuโ€ฆ

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ASTRA: Mapping Art-Technology Institutions via Conceptual Axes, Text Embeddings, and Unsupervised Clustering

Joonhyung Bae ยท 2026

The global landscape of art-technology institutions, including festivals, biennials, research labs, conferences, and hybrid organizations, has grown increasingly diverse, yet systematic frameworks forโ€ฆ

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