Oracle（甲骨文）

Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms

Alexandre Pacheco, Hanqing Zhao, Volker Strobel, Tarik Roukny, Gregory Dudek, Andreagiovanni Reina, Marco Dorigo

机构 * Swarm Oracle: Trustless Blockchain Agreements through Robot Swarms 纠错

Pruning the Paradox: How CLIP's Most Informative Heads Enhance Performance While Amplifying Bias

Avinash Madasu, Vasudev Lal, Phillip Howard

机构 * Intel Labs（英特尔实验室） ； Oracle（Oracle公司） ； Thoughtworks（Thoughtworks公司） 纠错

Probing the Representational Power of Sparse Autoencoders in Vision Models

Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng

机构 * Oracle ； Intel Labs（英特尔实验室） ； Oregon State University（俄勒冈州立大学） ； Thoughtworks 纠错

Comments ICCV 2025 Findings

Debias your Large Multi-Modal Model at Test-Time via Non-Contrastive Visual Attribute Steering

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Estelle Aflalo, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

机构 * Oracle ； Intel Labs（英特尔实验室） ； Thoughtworks 纠错

Comments 10 pages, 6 Figures, 8 Tables. arXiv admin note: text overlap with arXiv:2410.13976

Evaluating NL2SQL via SQL2NL

Mohammadtaher Safarzadeh, Afshin Oroojlooyjadid, Dan Roth

机构 * Oracle AI 纠错

Comments Accepted to EMNLP 2025

MoNaCo: More Natural and Complex Questions for Reasoning Across Dozens of Documents

Tomer Wolfson, Harsh Trivedi, Mor Geva, Yoav Goldberg, Dan Roth, Tushar Khot, Ashish Sabharwal, Reut Tsarfaty

机构 * University of Pennsylvania（宾夕法尼亚大学） ； Allen Institute for AI（人工智能研究院） ； Tel Aviv University（特拉维夫大学） ； Bar-Ilan University（巴伊兰大学） ； Oracle AI（Oracle人工智能） 纠错

Comments Accepted for publication in Transactions of the Association for Computational Linguistics (TACL), 2025. Authors pre-print

Hybrid AI for Responsive Multi-Turn Online Conversations with Novel Dynamic Routing and Feedback Adaptation

Priyaranjan Pattnayak, Amit Agarwal, Hansa Meghwani, Hitesh Laxmichand Patel, Srikant Panda

机构 * OCI, Oracle America Inc.（Oracle美洲公司） ； OCI, Oracle India（Oracle印度公司） 纠错

Comments Proceedings of the 4th International Workshop on Knowledge Augmented Methods for Natural Language Processing in NAACL 2025, pages 215 to 229, Albuquerque, New Mexico, USA. Association for Computational Linguistics

Journal ref Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing (KnowledgeNLP 2025), pp. 215 to 229, Association for Computational Linguistics, Albuquerque, New Mexico, May 2025

Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems

Hansa Meghwani, Amit Agarwal, Priyaranjan Pattnayak, Hitesh Laxmichand Patel, Srikant Panda

机构 * Oracle AI 纠错

Comments Accepted to ACL 2025

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use

Hitesh Laxmichand Patel, Amit Agarwal, Arion Das, Bhargava Kumar, Srikant Panda, Priyaranjan Pattnayak, Taki Hasan Rafi, Tejaswini Kumar, Dong-Kyu Chae

机构 * Oracle AI ； Indian Institute of Information Technology Ranchi（印度拉奇信息与技术学院） ； TD Securities（TD证券） ； Columbia University（哥伦比亚大学） ； Hanyang University（翰阳大学） 纠错

Comments Published in the Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2025), Industry Track, pages 558-582

Is (Selective) Round-To-Nearest Quantization All You Need?

Alex Kogan

机构 * Oracle Labs（Oracle实验室） 纠错

SQLong: Enhanced NL2SQL for Longer Contexts with LLMs

Dai Quoc Nguyen, Cong Duy Vu Hoang, Duy Vu, Gioacchino Tangari, Thanh Tien Vu, Don Dharmasiri, Yuan-Fang Li, Long Duong

机构 * Oracle Corporation（Oracle公司） 纠错

Comments Accepted to Table Representation Learning Workshop at ACL 2025

Adaptive Thresholding for Multi-Label Classification via Global-Local Signal Fusion

Dmytro Shamatrin

机构 * Oracle（Oracle公司） 纠错

Certifying Counterfactual Bias in LLMs

Isha Chaudhary, Qian Hu, Manoj Kumar, Morteza Ziyadi, Rahul Gupta, Gagandeep Singh

机构 * UIUC（伊利诺伊大学香槟分校） ； Amazon（亚马逊） ； Oracle Health（Oracle健康） 纠错

Comments Published at ICLR 2025

Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge

Xuan Shen, Peiyan Dong, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang

机构 * Oracle 纠错

Comments Accepted by AAAI 2024