Papers
Research papers from arXiv and related sources
How to formulate the $\mathbb{Z}_8$ topological invariant of Majorana fermion on the lattice
Topological invariants and their associated anomalies have played a crucial role in understanding low-energy phenomena in quantum field theories. In lattice gauge theory, the standard $\mathbb{Z}$-...
Sho Araki, Hidenori Fukaya, Tetsuya Onogi, Satoshi Yamaguchi
Interactive 3D visualization of surface roughness predictions in additive manufacturing: A data-driven framework
Surface roughness in Material Extrusion Additive Manufacturing varies across a part and is difficult to anticipate during process planning because it depends on both printing parameters and local s...
Engin Deniz Erkan, Elif Surer, Ulas Yaman
TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection
A significant number of anomalous nodes in the real world, such as fake news, noncompliant users, malicious transactions, and malicious posts, severely compromises the health of the graph data ecos...
Xiong Zhang, Hong Peng, Changlong Fu, Xin Jin, Yun Yang, Cheng Xie
The Virtuous Cycle: AI-Powered Vector Search and Vector Search-Augmented AI
Modern AI and vector search are rapidly converging, forming a promising research frontier in intelligent information systems. On one hand, advances in AI have substantially improved the semantic ac...
Jiuqi Wei, Quanqing Xu, Chuanhui Yang
TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) helps large language models (LLMs) answer knowledge-intensive and time-sensitive questions by conditioning generation on external evidence. However, most RAG sy...
Jiashuo Sun, Yixuan Xie, Jimeng Shi, Shaowen Wang, Jiawei Han
Testing Screened Modified Gravity with Strongly Lensed Gravitational Waves
Screening mechanisms are essential components in many modified gravity theories, which satisfy local tests of General Relativity (GR) and address cosmic acceleration on cosmological scales. The str...
Chengsheng Mu, Shuo Cao, Shuxun Tian, Xinyue Jiang, Chenfa Zheng, Dadian Cheng
Predictive Spectral Calibration for Source-Free Test-Time Regression
Test-time adaptation (TTA) for image regression has received far less attention than its classification counterpart. Methods designed for classification often depend on classification-specific obje...
Nguyen Viet Tuan Kiet, Huynh Thanh Trung, Pham Huy Hieu
Beyond Scaling: Assessing Strategic Reasoning and Rapid Decision-Making Capability of LLMs in Zero-sum Environments
Large Language Models (LLMs) have achieved strong performance on static reasoning benchmarks, yet their effectiveness as interactive agents operating in adversarial, time-sensitive environments rem...
Yang Li, Xing Chen, Yutao Liu, Gege Qi, Yanxian BI, Zizhe Wang, Yunjian Zhang, Yao Zhu
Can ChatGPT Generate Realistic Synthetic System Requirement Specifications? Results of a Case Study
System requirement specifications (SyRSs) are central, natural-language (NL) artifacts. Access to real SyRS for research purposes is highly valuable but limited by proprietary restrictions or confi...
Alex R. Mattukat, Florian M. Braun, Horst Lichter
TimberAgent: Gram-Guided Retrieval for Executable Music Effect Control
Digital audio workstations expose rich effect chains, yet a semantic gap remains between perceptual user intent and low-level signal-processing parameters. We study retrieval-grounded audio effect ...
Shihao He, Yihan Xia, Fang Liu, Taotao Wang, Shengli Zhang
Reading the Mood Behind Words: Integrating Prosody-Derived Emotional Context into Socially Responsive VR Agents
In VR interactions with embodied conversational agents, users' emotional intent is often conveyed more by how something is said than by what is said. However, most VR agent pipelines rely on speech...
SangYeop Jeong, Yeongseo Na, Seung Gyu Jeong, Jin-Woo Jeong, Seong-Eun Kim
Anomaly detection using surprisals
Anomaly detection methods are widely used but often rely on ad hoc rules or strong assumptions, and they often focus on tail events, missing ``inlier'' anomalies that occur in low-density gaps betw...
Rob J Hyndman, David T. Frazier
Curveball Steering: The Right Direction To Steer Isn't Always Linear
Activation steering is a widely used approach for controlling large language model (LLM) behavior by intervening on internal representations. Existing methods largely rely on the Linear Representat...
Shivam Raval, Hae Jin Song, Linlin Wu, Abir Harrasse, Jeff Phillips, Amirali Abdullah
Rescaling Confidence: What Scale Design Reveals About LLM Metacognition
Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confidence scale itself (typically 0--100) is rarely e...
Yuyang Dai
Reliable Tests of Faint-end UV Luminosity Functions in Strong Lensing Fields
Dark matter comprises ~85% of the entire mass of the Universe, but the fundamental nature of its constituent particles remains elusive. In this thesis, I test for two competitive dark matter models...
Jiashuo Zhang
Investor risk profiles of large language models
This paper investigates how large language models (LLMs) form and express investor risk profiles, a critical component of retail investment advising. We examine three LLMs (GPT, Gemini, and Llama) ...
Hanyong Cho, Geumil Bae, Jang Ho Kim
Constructing a Portfolio Optimization Benchmark Framework for Evaluating Large Language Models
This study introduces a benchmark framework for evaluating the financial decision-making capabilities of large language models (LLMs) through portfolio optimization problems with mathematically exp...
Hanyong Cho, Jang Ho Kim
TA-Mem: Tool-Augmented Autonomous Memory Retrieval for LLM in Long-Term Conversational QA
Large Language Model (LLM) has exhibited strong reasoning ability in text-based contexts across various domains, yet the limitation of context window poses challenges for the model on long-range in...
Mengwei Yuan, Jianan Liu, Jing Yang, Xianyou Li, Weiran Yan, Yichao Wu, Penghao Liang
Diagnosing and Repairing Citation Failures in Generative Engine Optimization
Generative Engine Optimization (GEO) aims to improve content visibility in AI-generated responses. However, existing methods measure contribution-how much a document influences a response-rather th...
Zhihua Tian, Yuhan Chen, Yao Tang, Jian Liu, Ruoxi Jia
ToolRosetta: Bridging Open-Source Repositories and Large Language Model Agents through Automated Tool Standardization
Reusing and invoking existing code remains costly and unreliable, as most practical tools are embedded in heterogeneous code repositories and lack standardized, executable interfaces. Although larg...
Shimin Di, Xujie Yuan, Hanghui Guo, Chaoqian Ouyang, Zhangze Chen, Ling Yue, Libin Zheng, Jia Zhu...