Papers
Research papers from arXiv and related sources
LaMoGen: Language to Motion Generation Through LLM-Guided Symbolic Inference
Human motion is highly expressive and naturally aligned with language, yet prevailing methods relying heavily on joint text-motion embeddings struggle to synthesize temporally accurate, detailed mo...
Junkun Jiang, Ho Yin Au, Jingyu Xiang, Jie Chen
Performance Evaluation of Open-Source Large Language Models for Assisting Pathology Report Writing in Japanese
The performance of large language models (LLMs) for supporting pathology report writing in Japanese remains unexplored. We evaluated seven open-source LLMs from three perspectives: (A) generation a...
Masataka Kawai, Singo Sakashita, Shumpei Ishikawa, Shogo Watanabe, Anna Matsuoka, Mikio Sakurai, ...
Leveraging Large Language Models and Survival Analysis for Early Prediction of Chemotherapy Outcomes
Chemotherapy for cancer treatment is costly and accompanied by severe side effects, highlighting the critical need for early prediction of treatment outcomes to improve patient management and infor...
Muhammad Faisal Shahid, Asad Afzal, Abdullah Faiz, Muhammad Siddiqui, Arbaz Khan Shehzad, Fatima ...
Quantitative 3D imaging of highly distorted micro-crystals using Bragg ptychography
Bragg coherent diffraction imaging (BCDI) fails to reliably retrieve phases in micro-crystals exhibiting strong strain inhomogeneities, which restricts its applicability. Here we show that three-di...
Peng Li, David Yang, Christoph Rau, Marc Allain, Felix Hofmann, Virginie Chamard
UtilityMax Prompting: A Formal Framework for Multi-Objective Large Language Model Optimization
The success of a Large Language Model (LLM) task depends heavily on its prompt. Most use-cases specify prompts using natural language, which is inherently ambiguous when multiple objectives must be...
Ofir Marom
Modeling Sequential Design Actions as Designer Externalization on an Infinite Canvas
Infinite canvas platforms are becoming central to contemporary design practice, enabling designers to externalize cognition through the spatial arrangement of multimodal artifacts. As AI agents inc...
Yejin Yun, Seung Won Lee, Jiin Choi, Kyung Hoon Hyun
Quantum Error Correction by Purification
We present a general-purpose quantum error correction primitive based on state purification via the SWAP test, which we refer to as purification quantum error correction (PQEC). This method operate...
Jonathan Raghoonanan, Tim Byrnes
Where Matters More Than What: Decoding-aligned KV Cache Compression via Position-aware Pseudo Queries
The Key-Value (KV) cache is crucial for efficient Large Language Models (LLMs) inference, but excessively long contexts drastically increase KV cache memory footprint. Existing KV cache compression...
Zhenxu Tian, Yi Su, Juntao Li, Min Zhang
AI Knows What's Wrong But Cannot Fix It: Helicoid Dynamics in Frontier LLMs Under High-Stakes Decisions
Large language models perform reliably when their outputs can be checked: solving equations, writing code, retrieving facts. They perform differently when checking is impossible, as when a clinicia...
Alejandro R Jadad
One Supervisor, Many Modalities: Adaptive Tool Orchestration for Autonomous Queries
We present an agentic AI framework for autonomous multimodal query processing that coordinates specialized tools across text, image, audio, video, and document modalities. A central Supervisor dyna...
Mayank Saini Arit Kumar Bishwas
ReHARK: Refined Hybrid Adaptive RBF Kernels for Robust One-Shot Vision-Language Adaptation
The adaptation of large-scale Vision-Language Models (VLMs) like CLIP to downstream tasks with extremely limited data -- specifically in the one-shot regime -- is often hindered by a significant "S...
Md Jahidul Islam
Highly Autonomous Cyber-Capable Agents: Anticipating Capabilities, Tactics, and Strategic Implications
This report introduces the concept of "Highly Autonomous Cyber-Capable Agents" (HACCAs), AI systems capable of autonomously conducting multi-stage cyber campaigns at a level comparable to today's t...
Jam Kraprayoon, Shaun Ee, Brianna Rosen, Yohan Matthew, Aditya Singh, Christopher Covino, Asher B...
Standard Condition Number-Based Detection for MIMO ISAC Systems under Noise Uncertainty
This paper presents a unified analytical and optimization framework for Standard Condition Number (SCN)-based detection in MIMO Integrated Sensing and Communication (ISAC) systems operating under n...
Alex Obando, Tharindu Udupitiya, Saman Atapattu, Kandeepan Sithamparanathan
Multi-Agent Collaboration for Automated Design Exploration on High Performance Computing Systems
Today's scientific challenges, from climate modeling to Inertial Confinement Fusion design to novel material design, require exploring huge design spaces. In order to enable high-impact scientific ...
Harshitha Menon, Charles F. Jekel, Kevin Korner, Brian Gunnarson, Nathan K. Brown, Michael Stees,...
Managing Cognitive Bias in Human Labeling Operations for Rare-Event AI: Evidence from a Field Experiment
Many operational AI systems depend on large-scale human annotation to detect rare but consequential events (e.g., fraud, defects, and medical abnormalities). When positives are rare, the prevalence...
Gunnar P. Epping, Andrew Caplin, Erik Duhaime, William R. Holmes, Daniel Martin, Jennifer S. True...
Tiny Aya: Bridging Scale and Multilingual Depth
Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in translation quality, ...
Alejandro R. Salamanca, Diana Abagyan, Daniel D'souza, Ammar Khairi, David Mora, Saurabh Dash, Vi...
Gen-Fab: A Variation-Aware Generative Model for Predicting Fabrication Variations in Nanophotonic Devices
Silicon photonic devices often exhibit fabrication-induced variations such as over-etching, underetching, and corner rounding, which can significantly alter device performance. These variations are...
Rambod Azimi, Yuri Grinberg, Dan-Xia Xu, Odile Liboiron-Ladouceur
KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation
Graph-based Retrieval-Augmented Generation (GraphRAG) constructs the Knowledge Graph (KG) from external databases to enhance the timeliness and accuracy of Large Language Model (LLM) generations.Ho...
Qizhi Chen, Chao Qi, Yihong Huang, Muquan Li, Rongzheng Wang, Dongyang Zhang, Ke Qin, Shuang Liang
Spherically-symmetrical vacuum solution in Freund-Nambu scalar-tensor gravity
Scalar--tensor theories of gravity provide a natural extension of general relativity and may predict naked singularities as alternative compact objects. In this work, we investigate a novel exact s...
Akbar Davlataliev, Bobur Turimov, Bobomurat Ahmedov, Yuri Vyblyi, Chengxun Yuan, Chen Zhou
Variance Estimation with Dependence and Heterogeneous Means
This paper considers the problem of estimating the variance of a sum of a triangular array of random vectors with heterogeneous means. When random vectors exhibit two-way cluster dependence or weak...
Luther Yap