Miniml Research: shaping frontier AI into production reality
Technical papers, experiments, and evaluations
Follow the Miniml team’s latest technical work across reasoning, long context, efficiency, and evaluation. We publish methods, results, and implementation insights built for real-world AI systems.
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DeCoRe: Decoding by Contrasting Retrieval Heads
February 28, 2026 • Miniml Research • EMNLP 2025 Findings
DeCoRe is a training-free decoding method that contrasts retrieval heads to curb hallucinations in context-grounded generation.
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FLARE: Faithful Logic-Aided Reasoning and Exploration
January 28, 2026 • Miniml Research • Empirical Methods in Natural Language Processing (EMNLP)
FLARE pairs LLM planning with logic programming and simulation to improve faithfulness in multi-step reasoning.
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GRADA: Graph-based Reranker against Adversarial Documents Attack
January 28, 2026 • Miniml Research
GRADA defends RAG pipelines by reranking retrieved documents to resist adversarial injections while preserving accuracy.
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MMLongBench: Benchmarking Long-Context Vision-Language Models
January 28, 2026 • Miniml Research
MMLongBench evaluates long-context VLMs across tasks and image types, revealing gaps in long-context multimodal reasoning.
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Neuro-symbolic Diffusion Models
January 28, 2026 • Miniml Research
NeSyDMs use discrete diffusion to model dependencies among symbols, improving accuracy and calibration for neurosymbolic prediction.
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Activation Sparsity and Enterprise AI Efficiency
January 18, 2026 • Miniml
Activation sparsity suggests large language models can become more efficient at inference without sacrificing capability.
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Neurosymbolic reasoning shortcuts under the independence assumption
September 23, 2025 • Miniml Research
Why the independence assumption in NeSy predictors can hide uncertainty and lead to shortcut reasoning.
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Q-Filters: Leveraging QK geometry for efficient KV cache compression
August 12, 2025 • Miniml Research
Q-Filters compress the KV cache at inference by filtering keys using QK geometry, without training.
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NOISER: Bounded input perturbations for attributing large language models
April 3, 2025 • Miniml Research • Conference on Language Modeling (COLM)
NOISER estimates token attributions by injecting bounded noise into embeddings to test output sensitivity.
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PosterSum: A multimodal benchmark for scientific poster summarization
February 24, 2025 • Miniml Research
PosterSum introduces a large multimodal benchmark for summarizing scientific posters into abstracts.