Papers
Research papers from arXiv and related sources
MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
Supervised machine learning describes the practice of fitting a parameterized model to labeled input-output data. Supervised machine learning methods have demonstrated promise in learning efficient...
Atticus Rex, Elizabeth Qian, David Peterson
Dynamic analysis enhances issue resolution
Translating natural language descriptions into viable code fixes remains a fundamental challenge in software engineering. While the proliferation of agentic large language models (LLMs) has vastly ...
Mingwei Liu, Zihao Wang, Zhenxi Chen, Zheng Pei, Yanlin Wang, Zibin Zheng
DTVI: Dual-Stage Textual and Visual Intervention for Safe Text-to-Image Generation
Text-to-Image (T2I) diffusion models have demonstrated strong generation ability, but their potential to generate unsafe content raises significant safety concerns. Existing inference-time defense ...
Binhong Tan, Zhaoxin Wang, Handing Wang
Set-Theoretic Types for Erlang: Theory, Implementation, and Evaluation
Erlang's dynamic typing discipline can lead to runtime errors that persist even after process restarts. Some of these runtime errors could be prevented through static type checking. While Erlang pr...
Albert Schimpf, Stefan Wehr, Annette Bieniusa
Tuning Real-World Image Restoration at Inference: A Test-Time Scaling Paradigm for Flow Matching Models
Although diffusion-based real-world image restoration (Real-IR) has achieved remarkable progress, efficiently leveraging ultra-large-scale pre-trained text-to-image (T2I) models and fully exploitin...
Purui Bai, Junxian Duan, Pin Wang, Jinhua Hao, Ming Sun, Chao Zhou, Huaibo Huang
Identical, independent quantum weak measurements violate objective realism
We demonstrate violation of objective realism in quantum world using unconstrained weak measurements. Instead of limited Leggett-Garg approach with artificial bounds on the observed values, we assu...
Tomasz Rybotycki, Tomasz Białecki, Josep Batle, Bartłomiej Zglinicki, Adam Szereszewski, Wolfgang...
On the Challenges and Opportunities of Learned Sparse Retrieval for Code
Retrieval over large codebases is a key component of modern LLM-based software engineering systems. Existing approaches predominantly rely on dense embedding models, while learned sparse retrieval ...
Simon Lupart, Maxime Louis, Thibault Formal, Hervé Déjean, Stéphane Clinchant
VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models
Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to robotic control signals. This "black-box" mapping forces a single forward pass to simul...
Zixuan Wang, Yuxin Chen, Yuqi Liu, Jinhui Ye, Pengguang Chen, Changsheng Lu, Shu Liu, Jiaya Jia
CRPS-Optimal Binning for Conformal Regression
We propose a method for non-parametric conditional distribution estimation based on partitioning covariate-sorted observations into contiguous bins and using the within-bin empirical CDF as the pre...
Paolo Toccaceli
Surfacing and Applying Meaning: Supporting Hermeneutical Autonomy for LGBTQ+ People in Taiwan
After Taiwan's legalization of same-sex marriage in 2019, LGBTQ+ communities continue to face hostility on social media. Using the lens of hermeneutical injustice and autonomy, we examine how techn...
Yi-Tong Chen, En-Kai Chang, Nanyi Bi, Nitesh Goyal
Speed by Simplicity: A Single-Stream Architecture for Fast Audio-Video Generative Foundation Model
We present daVinci-MagiHuman, an open-source audio-video generative foundation model for human-centric generation. daVinci-MagiHuman jointly generates synchronized video and audio using a single-st...
SII-GAIR, Sand. ai, :, Ethan Chern, Hansi Teng, Hanwen Sun, Hao Wang, Hong Pan, Hongyu Jia, Jia...
SecureBreak -- A dataset towards safe and secure models
Large language models are becoming pervasive core components in many real-world applications. As a consequence, security alignment represents a critical requirement for their safe deployment. Altho...
Marco Arazzi, Vignesh Kumar Kembu, Antonino Nocera
Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe
Reinforcement Learning (RL) is essential for evolving Large Language Models (LLMs) into autonomous agents capable of long-horizon planning, yet a practical recipe for scaling RL in complex, multi-t...
Xixi Wu, Qianguo Sun, Ruiyang Zhang, Chao Song, Junlong Wu, Yiyan Qi, Hong Cheng
Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
Fine-tuning large language models for domain-specific tasks such as medical text summarization demands substantial computational resources. Parameter-efficient fine-tuning (PEFT) methods offer prom...
Ulugbek Shernazarov, Rostislav Svitsov, Bin Shi
BHDD: A Burmese Handwritten Digit Dataset
We introduce the Burmese Handwritten Digit Dataset (BHDD), a collection of 87,561 grayscale images of handwritten Burmese digits in ten classes. Each image is 28x28 pixels, following the MNIST form...
Swan Htet Aung, Hein Htet, Htoo Say Wah Khaing, Thuya Myo Nyunt
Structured-light propagation in a medium with uniform torsion: polarization textures, geometric birefringence, and beam-resolved optical activity
We investigate finite-width optical-beam propagation in a medium with uniform torsion described by the geometric theory of a continuous distribution of screw dislocations. Starting from the Riemann...
Edilberto O. Silva
Unified Spatiotemporal Token Compression for Video-LLMs at Ultra-Low Retention
Video large language models (Video-LLMs) face high computational costs due to large volumes of visual tokens. Existing token compression methods typically adopt a two-stage spatiotemporal compressi...
Junhao Du, Jialong Xue, Anqi Li, Jincheng Dai, Guo Lu
You See It, They Don't: An Exploratory Study of User-to-User Variation in Instagram Comments
In March 2025, Meta announced a new AI system to rank the order of the comments shown to Instagram users. With existing research showing how feed personalization systems can lead to increased polar...
Brahmani Nutakki, Manon Lilott Kempermann, Ingmar Weber
Parsimonious Subset Selection for Generalized Linear Models with Biomedical Applications
High-dimensional biomedical studies require models that are simultaneously accurate, sparse, and interpretable, yet exact best subset selection for generalized linear models is computationally intr...
Anant Mathur, Benoit Liquet, Samuel Muller, Sarat Moka
Look, Listen and Segment: Towards Weakly Supervised Audio-visual Semantic Segmentation
Audio-Visual Semantic Segmentation (AVSS) aligns audio and video at the pixel level but requires costly per-frame annotations. We introduce Weakly Supervised Audio-Visual Semantic Segmentation (WSA...
Chengzhi Li, Heyan Huang, Ping Jian, Yanghao Zhou