From the 1 of 79 linked papers with an AI index.
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LLM-Guided Evolution for Medical Decision Pipelines
Ivan Sviridov, Artem Oskin, Ivan Panin +4
Adapting large language models (LLMs) to clinical workflows often requires costly fine-tuning or manual prompt and pipeline engineering. We study LLM-guided MAP-Elites evolution as…
OCC-RAG: Optimal Cognitive Core for Faithful Question Answering
Maksim Savkin, Mikhail Goncharov, Alexander Gambashidze +7
Recent progress in the development of language models has been defined by scale, with each generation absorbing more of the world's knowledge into its weights. However, many practi…
Logit-KL Flow Matching: Non-Autoregressive Text Generation via Sampling-Hybrid Inference
Egor Sevriugov, Nikita Dragunov, Anton Razzhigaev +2
Non-autoregressive (NAR) language models offer notable efficiency in text generation by circumventing the sequential bottleneck of autoregressive decoding. However, accurately mode…
Exploring the Hidden Capacity of LLMs for One-Step Text Generation
Gleb Mezentsev, Ivan Oseledets
A recent study showed that large language models (LLMs) can reconstruct surprisingly long texts - up to thousands of tokens - via autoregressive generation from just one trained in…
CLARITY: Clinical Assistant for Routing, Inference, and Triage
Vladimir Shaposhnikov, Aleksandr Nesterov, Ilia Kopanichuk +7
We present CLARITY (Clinical Assistant for Routing, Inference and Triage), an AI-driven platform designed to facilitate patient-to-specialist routing, clinical consultations, and s…
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Andrey Galichin, Alexey Dontsov, Polina Druzhinina +4
Recent LLMs like DeepSeek-R1 have demonstrated state-of-the-art performance by integrating deep thinking and complex reasoning during generation. However, the internal mechanisms b…