Donating llm-d to the Cloud Native Computing Foundation
News
Peter Hess
Generative AI
Generative AI is revolutionizing how the world computes, but there are still roadblocks for scaling to solve real business problems. At IBM Research, we’re working on trustworthy models, software, and infrastructure to allow any business to harness the power of generative AI.
Our work
How IBM Granite became a leader in responsible AI
ExplainerKim MartineauAI for seeing the forest — and the trees
NewsKim MartineauLLMs have model cards. Now, benchmarks do, too
ReleaseKim MartineauThe quest to teach LLMs how to count
ResearchKim MartineauIBM Granite 4.0: Hyper-efficient, high performance hybrid models for India
Technical noteRudra Murthy, Rameswar Panda, Jaydeep Sen, and Amith Singhee- See more of our work on Generative AI
Publications
Context-Aware Visual Multi-Turn Conversation Generation from Wikipedia and Wikidata
- Basel Shbita
- Pengyuan Li
- et al.
- 2026
- ESWC 2026
Conference paperAdaptive Decoding via Test-Time Policy Learning for Self-Improving Generation
- Asmita Bhardwaj
- Yuya Ong
- et al.
- 2026
- ICLR 2026
Workshop paperEvaluating Ill-Defined Tasks in Large Language Models
- 2026
- ICLR 2026
Workshop paperLogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
- Farhan Ahmed
- Yuya Ong
- et al.
- 2026
- ICLR 2026
Workshop paperDropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
- Jenny Huang
- Yunyi Shen
- et al.
- 2026
- ICLR 2026
Conference paperTHOMPSON SAMPLING VIA FINE-TUNING OF LLMS
- Nicolas Menet
- Aleksandar Terzic
- et al.
- 2026
- ICLR 2026
Conference paper