ServiceNow Research

Trustworthiness

StarVector: Generating Scalable Vector Graphics Code from Images and Text
StarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility. Previous SVG generation …
Computer Vision and Pattern Recognition (CVPR),  2025.
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Unpacking Trust Dynamics in the LLM Supply Chain: An Empirical Exploration to Foster Trustworthy LLM Production & Use
Unpacking Trust Dynamics in the LLM Supply Chain: An Empirical Exploration to Foster Trustworthy LLM Production & Use
Research on trust in AI is limited to several trustors (e.g., end-users) and trustees (especially AI systems), and empirical …
CHI conference on Human Factors in Computing Systems (CHI),  2025.
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StarVector: Generating Scalable Vector Graphics Code from Images and Text
StarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility. Previous SVG generation …
AAAI Demos,  2025.
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BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks
BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks
Vision and language models that can accurately understand both images and text are crucial for deeper document understanding. These …
Workshop at the Neural Information Processing Systems (NeurIPS),  2024.
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Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Deployed machine learning systems require some mechanism to detect out-of-distribution (OOD) inputs. Existing research mainly focuses …
NeurIPS Datasets and Benchmarks Track (NeurIPS Datasets),  2024.
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Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering
Retriever-augmented instruction-following models are attractive alternatives to fine-tuned approaches for information-seeking tasks …
Annual Meeting of the Association for Computational Linguistics (ACL),  2024.
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An Empirical Exploration of Trust Dynamics in LLM Supply Chains
An Empirical Exploration of Trust Dynamics in LLM Supply Chains
With the widespread proliferation of AI systems, trust in AI is an important and timely topic to navigate. Researchers so far have …
Conference on Human Factors in Computing Systems (ACM-CHI),  2024.
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Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. …
Conference on Human Factors in Computing Systems (ACM-CHI),  2024.
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Explainable, Sensible and Virtuous Workplace Chatbots
We outline three research directions towards the practical implementation of explainable, sensible and virtuous chatbots for the …
Montreal AI Symposium (MAIS),  2022.
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Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews
Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews
The artificial intelligence research community is continuing to grapple with the ethics of their work by encouraging researchers to …
AAAI/ACM Conference on AI, Ethics, and Society (AIES),  2022.
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