Miniml Research
Technical papers, experiments, and evaluations
Advancing AI across reasoning, long context, efficiency, and evaluation, with research that strengthens real-world systems.
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Complex Query Answering with Neural Link Predictors
March 6, 2026 • Miniml
This paper presents a differentiable framework that uses pre-trained neural link predictors to answer complex logical queries on incomplete knowledge graphs with higher accuracy and much less training data.
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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 • ICLR 2021
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.