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Author

Branislav Kveton

2 papers indexed here

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DISCO: Distributed Long Context Scaling with Grounding-Reasoning Disaggregation

Inspired by distributed computing frameworks like Apache Spark, DISCO partitions long context across a fleet of Worker LLMs dedicated exclusively to parallel, localized grounding, establishing a highly efficient paradigm for robust long-context inference.

Guan-Zheng Chen, Viet Dac Lai, Subhojyoti Mukherjee et al. · 0 citations
#machine learning Preprint Sep 2026

Online Learning with LLM Experts from Limited Feedback

We study adaptive routing of prompts to large language model (LLM) experts to maximize response quality in an online setting with limited feedback. We formulate it as a bandit problem with $K$ actions that represent experts and $d$ features that encode prompts, over a horizon of $T$ rounds. We propose algorithms that s...

Wei Wang, Soumyabrata Pal, Koyel Mukherjee et al. · 0 citations

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