Papers
QiMeng-PRepair: Precise Code Repair via Edit-Aware Reward Optimization
Changxin Ke, Rui Zhang, Jiaming Guo et al.
Q-MoFusion: A Quantum Classifier for Masquito Species Classification (Student Abstract)
Vishesh Kumar, Ahana Chanda, Poulomi Bhattacharya et al.
Qomhrá: A Bilingual Irish and English Large Language Model
Joseph McInerney, Khanh-Tung Tran, Liam Lonergan et al.
QRShield: Exploiting Vulnerabilities of Latent Diffusion Models for Preventing AI Art Plagiarism
Xunyue Mo, Weibin Wu, Qingrui Tu et al.
QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models
Maximilian Kreutner, Jens Rupprecht, Georg Ahnert et al.
QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation
Chenhui Xu, Fuxun Yu, Jinjun Xiong et al.
Qualitative Analysis of ω-Regular Objectives on Robust MDPs
Ali Asadi, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady et al.
Quality-Aware Adversarial Ensemble for Singer Identification in 1960s Tamil Film Music
Sathiyakugan Balakrishnan, Uthayasanker Thayasivam
Quality-aware and Soft Consistency Driven Representation Fusion for Incomplete Multi-view Multi-label Classification
Yadong Liu, Waikeung Wong, Yulong Chen et al.
Quality-Aware Language-Conditioned Local Auto-Regressive Anomaly Synthesis and Detection
Long Qian, Bingke Zhu, Yingying Chen et al.
QuanTaxo: A Quantum Approach to Self-Supervised Taxonomy Expansion
Sahil Mishra, Avi Patni, Niladri Chatterjee et al.
Quantifying Aleatoric Uncertainty of In-Context Learning for Robust Measure of LLM Prediction Confidence
Jinseok Chung, Minkyoung Song, Hyunji Jung et al.
Quantifying and Improving Adaptivity in Conformal Prediction Through Input Transformations
Sooyong Jang, Insup Lee
Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
Shiping Yang, Jie Wu, Wenbiao Ding et al.
Quantifying and Mitigating Socially Desirable Responding in LLMs: A Desirability-Matched Graded Forced-Choice Psychometric Study
Kensuke Okada, Yui Furukawa, Kyosuke Bunji
Quantifying and Understanding Uncertainty in Large Reasoning Models
Yangyi Li, Chenxu Zhao, Mengdi Huai
Quantifying Data Contamination in Psychometric Evaluations of LLMs
Jongwook Han, Woojung Song, Jonggeun Lee et al.
Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models
Arash Asgari, Huan Wu, Amirreza Naziri et al.
Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference
Han Yuan, Yue Zhao, Li Zhang et al.
Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation
Klaudia Thellmann, Bernhard Stadler, Michael Färber et al.
Quantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast Objects
Yixin Zhang, Nicholas Konz, Kevin Kramer et al.