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research#llm📝 BlogAnalyzed: Jan 21, 2026 18:03

Revolutionizing Image Generation: LLM Takes the Reins in SDXL!

Published:Jan 21, 2026 13:11
1 min read
r/StableDiffusion

Analysis

This is a truly exciting development! By replacing CLIP with an LLM in SDXL, the researcher has potentially unlocked a new level of control and nuance in image generation. The use of a smaller, specialized model to transform the LLM's hidden state is a clever and efficient approach, hinting at faster and more flexible workflows.
Reference

“My theory, is that CLIP is the bottleneck as it struggles with spatial adherence (things like left of, right), negations in the positive prompt (e.g. no moustache), contetx length limit (77 token limit) and natural language limitations. So, what if we could apply an LLM to directly do conditioning, and not just alter ('enhance') the prompt?”

Permalinkr/StableDiffusion
Paper#llm🔬 ResearchAnalyzed: Jan 3, 2026 16:54

Explainable Disease Diagnosis with LLMs and ASP

Published:Dec 30, 2025 01:32
1 min read
ArXiv

Analysis

This paper addresses the challenge of explainable AI in healthcare by combining the strengths of Large Language Models (LLMs) and Answer Set Programming (ASP). It proposes a framework, McCoy, that translates medical literature into ASP code using an LLM, integrates patient data, and uses an ASP solver for diagnosis. This approach aims to overcome the limitations of traditional symbolic AI in healthcare by automating knowledge base construction and providing interpretable predictions. The preliminary results suggest promising performance on small-scale tasks.
Reference

“McCoy orchestrates an LLM to translate medical literature into ASP code, combines it with patient data, and processes it using an ASP solver to arrive at the final diagnosis.”

PermalinkArXiv