RUNE Lab

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authored a paper 4 months ago

Guarded Query Routing for Large Language Models

Paper • 2505.14524 • Published May 20, 2025 • 2

authored 6 papers 7 months ago

Continual Quantization-Aware Pre-Training: When to transition from 16-bit to 1.58-bit pre-training for BitNet language models?

Paper • 2502.11895 • Published Feb 17, 2025 • 3

What makes a language easy to deep-learn? Deep neural networks and humans similarly benefit from compositional structure

Paper • 2302.12239 • Published Feb 23, 2023 • 1

Dynaword: From One-shot to Continuously Developed Datasets

Paper • 2508.02271 • Published Aug 4, 2025 • 15

GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding

Paper • 2311.09707 • Published Nov 16, 2023

When are 1.58 bits enough? A Bottom-up Exploration of BitNet Quantization

Paper • 2411.05882 • Published Nov 8, 2024 • 1

CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model

Paper • 1902.06423 • Published Feb 18, 2019