Natural Language Processing
Much of the information that can help transform enterprises is locked away in text, like documents, tables, and charts. We’re building advanced AI systems that can parse vast bodies of text to help unlock that data, but also ones flexible enough to be applied to any language problem.
Our work
A new kind of adapter helps LLMs get their words out faster
ResearchKim MartineauIBM’s safety checkers top a new AI benchmark
NewsKim MartineauBeeAI now has multiple agents, and a standardized way for them to talk
ResearchKim MartineauIBM’s Mikhail Yurochkin wants to make AI’s “cool” factor tangible
ResearchKim MartineauIBM Granite now has eyes
ResearchKim MartineauA benchmark for evaluating conversational RAG
ResearchKim Martineau- See more of our work on Natural Language Processing
Publications
Challenges and Remedies of Domain-Specific Classifiers as LLM Guardrails: Self-Harm as a Case Study
- Bing Zhang
- Guang-Jie Ren
- 2025
- NAACL 2025
Are Large Language Models Effective in Clinical Trial Design? A Study on Baseline Feature Generation
- Nafis Neehal
- Bowen Wang
- et al.
- 2025
- NAACL 2025
The Literary Canons of Large-Language Models: An Exploration of the Frequency of Novel and Author Generations Across Gender, Race and Ethnicity, and Nationality
- Paulina Toro Isaza
- Nalani Kopp
- 2025
- NAACL 2025
MILU: A Multi-task Indic Language Understanding Benchmark
- Sshubam Verma
- Mohammed Safi Ur Rahman
- et al.
- 2025
- NAACL 2025
Benchmarking and Building Zero-Shot Hindi Retrieval Model with Hindi-BEIR and NLLB-E5
- Arkadeep Acharya
- Rudra Murthy Venkataramana
- et al.
- 2025
- NAACL 2025
Designing and implementing LLM guardrails components in production environments
- Mateus Do Amor Devino Pereira
- Evaline Ju
- et al.
- 2025
- CAIN 2025