Henil Shalin Panchal — accepted AI-conference papers

2025

Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents

Qiusi Zhan, Richard Fang, Henil Shalin Panchal, Daniel Kang

NAACL 2025findings

Large Language Model (LLM) agents exhibit remarkable performance across diverse applications by using external tools to interact with environments. However, integrating external tools introduces security risks, such as indirect prompt injection (IPI) attacks. Despite defenses designed for IPI attack…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2025

MMTEB: Massive Multilingual Text Embedding Benchmark

Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, Márton Kardos, Ashwin Mathur, David Stap +76

ICLR 2025poster

Text embeddings are typically evaluated on a narrow set of tasks, limited in terms of languages, domains, and task types. To circumvent this limitation and to provide a more comprehensive evaluation, we introduce the Massive Multilingual Text Embedding Benchmark (MMTEB) -- a large-scale community-dr…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗