OracleProto is a reproducible framework that uses model-cutoff alignment, temporal masking, and leakage detection to create low-leakage benchmarks for LLM native forecasting from past events.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Moondream Segmentation achieves 80.2% cIoU on RefCOCO by autoregressively decoding paths from referring expressions and using RL to refine masks, plus releases a cleaned RefCOCO-M dataset.
Conditions are derived under which the completion DM(RS) of rough sets from reflexive relations forms a regular pseudocomplemented Kleene algebra or a completely distributive double Stone algebra.
citing papers explorer
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OracleProto: A Reproducible Framework for Benchmarking LLM Native Forecasting via Knowledge Cutoff and Temporal Masking
OracleProto is a reproducible framework that uses model-cutoff alignment, temporal masking, and leakage detection to create low-leakage benchmarks for LLM native forecasting from past events.
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Moondream Segmentation: From Words to Masks
Moondream Segmentation achieves 80.2% cIoU on RefCOCO by autoregressively decoding paths from referring expressions and using RL to refine masks, plus releases a cleaned RefCOCO-M dataset.
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Kleene and Stone algebras of rough sets induced by reflexive relations
Conditions are derived under which the completion DM(RS) of rough sets from reflexive relations forms a regular pseudocomplemented Kleene algebra or a completely distributive double Stone algebra.