# Capital One at ACL 2026

DevFeed: [Capital One at ACL 2026](<https://devfeed.tech/articles/capital-one-at-acl-2026-22571.md>)

Original publisher: [Read original article](<https://medium.com/capital-one-tech/capital-one-at-acl-2026-ad9c245333fe?source=rss----3db3a67cb648---4>)

Author: Capital One Tech

Published: 2026-07-01T15:28:51Z

Content type: article

Language: en

Sources: [Capital One Tech](<https://devfeed.tech/sources/capital-one-tech.md>)

Topics: [Natural language processing](<https://devfeed.tech/topics/nlp.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [LLM security](<https://devfeed.tech/topics/llm-security.md>), [Machine Learning, Security Attacks](<https://devfeed.tech/topics/machine-learning-security-attacks.md>), [Reinforcement learning](<https://devfeed.tech/topics/reinforcement-learning.md>), [Jailbreak](<https://devfeed.tech/topics/jailbreak.md>), [Security](<https://devfeed.tech/topics/security.md>), [Routing (disambiguation)](<https://devfeed.tech/topics/routing.md>), [datasets](<https://devfeed.tech/topics/datasets.md>)

Tags: [2026](<https://devfeed.tech/tags/2026.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-ml](<https://devfeed.tech/tags/ai-ml.md>), [ai-research](<https://devfeed.tech/tags/ai-research.md>), [conference](<https://devfeed.tech/tags/conference.md>), [jailbreak](<https://devfeed.tech/tags/jailbreak.md>), [llm-security](<https://devfeed.tech/tags/llm-security.md>), [natural-language-processing](<https://devfeed.tech/tags/natural-language-processing.md>), [paper](<https://devfeed.tech/tags/paper.md>), [partners](<https://devfeed.tech/tags/partners.md>), [red-teaming](<https://devfeed.tech/tags/red-teaming.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [research](<https://devfeed.tech/tags/research.md>), [science](<https://devfeed.tech/tags/science.md>)

## AI overview

Capital One describes its accepted ACL 2026 research on natural language processing, including work on adaptive LLM red teaming, query-only model routing with generated data, and language identification on web data. The article also highlights collaboration with academic partners.

## Source excerpt

Discover how Capital One is advancing state-of-the-art AI/ML science through collaborative natural language processing research.Advancing AI and NLP Frontiers at ACL 2026 As language models grow more deeply integrated into technology ecosystems, pioneering robust, efficient, and reliable Natural Language Processing (NLP) techniques becomes paramount. Capital One continues to invest in state-of-the-art AI/ML science through deep multi-sector collaboration and peer-reviewed research. At the upcoming Annual Meeting of the Association for Computational Linguistics (ACL 2026), Capital One researchers and academic partners will showcase novel findings stretching from LLM security to multilingual capabilities. Through the Science & Academic Partnerships program, Capital One bridges industry needs with academic expertise, funding critical university research and engineering solutions that make technology safer and more powerful. Our accepted publications at ACL 2026 demonstrate this thriving flywheel of talent and collaborative innovation across multiple research categories. Main Conference Research Adaptive Instruction Composition for Automated LLM Red Teaming Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection Capital One Authors: Jesse Zymet, Swapnil Shinde, Sahil Wadhwa, Andy Luo Overview: Standard red teaming approaches often struggle with a limited range of jailbreak strategies or rely on ineffective, randomized crowd-sourced tactics. This paper introduces a novel framework -- Adaptive Instruction Composition -- that utilizes reinforcement learning and a neural contextual bandit to tailor attack compositions dynamically, balancing diversity and effectiveness to proactively uncover target model vulnerabilities. Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection Capital One Authors: Genta Winata, Sambit Sahu, Supriyo Chakraborty, Shixiong Zhang Overview: Emerging from our gifted research collaboration