Multi-level context Modeling for consistent expert selection in Mixture-of-Experts

arXiv:2607.16427 · cs.CL · Submitted 2026-07-17 · Read on arXiv

cs.CL

Submitted: 2026-07-17

Updated: 2026-09-27

Terminology

• Consistency — 23× in this paper · explained in 3 episodes
• Transformer — 15× in this paper · explained in 2 episodes
• Alignment — 10× in this paper · explained in 1 episode
• Fine-Tuning — 10× in this paper · explained in 5 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Accuracy — 7× in this paper · explained in 1 episode
• Mixture of Experts — 7× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Perplexity — 6× in this paper · explained in 3 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Semantic Alignment — 6× in this paper · explained in 3 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Hypernetwork — 3× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) — 3× in this paper · explained in 7 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Transformer Models — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Sparse Mixture-of-Experts — 2× in this paper
• Tokenization — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Corpus of Linguistic Acceptability — 1× in this paper
• F1 Score — 1× in this paper · explained in 3 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Quora Question Pairs — 1× in this paper
• Recognizing Textual Entailment — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Winograd Natural Language Inference — 1× in this paper

Sources

• Routing in Sparsely-gated Language Models responds to Context
• Revisiting MoE and Dense Speed-Accuracy Comparisons for LLM Training
• Gini Coefficient as a Unified Metric for Evaluating Many-versus-Many Similarity in Vector Spaces
• Expert-Token Resonance MoE: Bidirectional Routing with Efficiency Affinity-Driven Active Selection
• Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
• Pointer Sentinel Mixture Models
• Load Balancing Mixture of Experts with Similarity Preserving Routers

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