9 citations · 12 across the 16 of their papers we have counts for
4 papers · 1 filter
Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains
Raeid Saqur, Christoph Bergmeir, Blanka Horvath +3
We argue that the current practice of evaluating AI/ML time-series forecasting models, predominantly on benchmarks characterized by strong, persistent periodicities and seasonaliti…
LLM Library Learning Fails: A LEGO-Prover Case Study
Ian Berlot-Attwell, Frank Rudzicz, Xujie Si
Recent advancements in the coding, reasoning, and tool-using abilities of LLMs have spurred interest in library learning (i.e., online learning through the creation, storage, and r…
Library Learning Doesn't: The Curious Case of the Single-Use "Library"
Ian Berlot-Attwell, Frank Rudzicz, Xujie Si
Advances in Large Language Models (LLMs) have spurred a wave of LLM library learning systems for mathematical reasoning. These systems aim to learn a reusable library of tools, suc…
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
Raeid Saqur, Anastasis Kratsios, Florian Krach +5
We propose MoE-F - a formalized mechanism for combining pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting…