Latest Research
The Malaysian Election Corpus (MECo): Federal and State-Level Election Results from 1955 to 2025
Empirical research and public knowledge on Malaysia's elections have long been constrained by a lack of high-quality open data, particularly in the absence of a Freedom of Information framework.
Computers and Society Applications
Scheduled Jacobian Chaining
This paper addresses the efficient computation of Jacobian matrices for programs composed of sequential differentiable subprograms.
Discrete Mathematics Distributed, Parallel, and Cluster Computing Data Structures and Algorithms Combinatorics
CPP-DIP: Multi-objective Coverage Path Planning for MAVs in Dispersed and Irregular Plantations
A density-aware waypoint strategy is applied: Kernel Density Estimation (KDE) is used to reduce redundant waypoints in dense regions, while a greedy algorithm ensures complete coverage in sparse areas.
Robotics
HEXGEN-TEXT2SQL: Optimizing LLM Inference Request Scheduling for Agentic Text-to-SQL Workflow
In this paper, we introduce HEXGEN-TEXT2SQL, a novel framework designed explicitly to schedule and execute agentic multi-stage LLM-based Text-to-SQL workflows on heterogeneous GPU clusters that handle multi-tenant end-to-end queries.
Databases
Empowering Scientific Workflows with Federated Agents
To demonstrate the breadth of applications that can be supported by agentic workflow designs, we also present case studies in materials discovery, decentralized learning, and information extraction in which agents are deployed across diverse HPC systems.
Multiagent Systems Distributed, Parallel, and Cluster Computing
QUIC-Exfil: Exploiting QUIC's Server Preferred Address Feature to Perform Data Exfiltration Attacks
Whereas existing data exfiltration techniques, such as TLS and DNS-based exfiltration, can be detected on a firewall level, QUIC-based data exfiltration is more difficult to detect, since changes in IP addresses and ports are inherent to the protocol's normal behavior.
Cryptography and Security
Cross-Problem Solving for Network Optimization: Is Problem-Aware Learning the Key?
qiyu3816/pad
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This limitation reveals a key gap between current methods and human solving - the inability to recognize and understand problem characteristics.
Networking and Internet Architecture
Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware
MARIN consists of two phases: Hierarchical Dependency Mining, which analyzes local and global dependencies of the current function, aiming to supplement comprehensive project context in LLMs input, and Dependency Constrained Decoding, which utilizes mined dependencies to adaptively constrain the generation process, aiming to ensure the generated APIs align with the projects specifications.
Software Engineering
AutoPatch: Multi-Agent Framework for Patching Real-World CVE Vulnerabilities
Large Language Models (LLMs) have emerged as promising tools in software development, enabling automated code generation and analysis.
Cryptography and Security
QStore: Quantization-Aware Compressed Model Storage
A straightforward approach is to maintain a separate file for each model precision (e. g., INT8, BF16), which is indeed the approach taken by many model providers such as HuggingFace and Ollama.
Databases
