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Model Merging

6 articles · Page 1 of 1
DeepHub IMBA
DeepHub IMBA
Jun 17, 2026 · Artificial Intelligence

How a 1.5B Parameter Model Can Add External Knowledge to Any Frozen LLM

The article analyzes MEMO, a framework that equips a frozen large language model with a lightweight 1.5B‑parameter memory model fine‑tuned on a target corpus, detailing its architecture, five‑step data synthesis pipeline, structured inference protocol, experimental advantages over RAG and fine‑tuning, as well as its limitations and future research directions.

Fine-tuningKnowledge IntegrationLLM
0 likes · 19 min read
How a 1.5B Parameter Model Can Add External Knowledge to Any Frozen LLM
Machine Heart
Machine Heart
Jun 7, 2026 · Artificial Intelligence

FusionRoute: Token-Level Expert Routing and Self-Correction for Multi-LLM Collaboration

FusionRoute introduces a token‑level routing framework that dynamically selects the most suitable expert LLM for each token and adds a complementary generation step, enabling fine‑grained, stable multi‑model collaboration that outperforms existing sequence‑level and expert‑selection methods across diverse benchmarks.

AI researchModel Mergingexpert routing
0 likes · 11 min read
FusionRoute: Token-Level Expert Routing and Self-Correction for Multi-LLM Collaboration
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Apr 18, 2026 · Artificial Intelligence

Model Ability Gets Squeezed Out in Multi‑Task Learning—How ESM Preserves It (CVPR 2026)

The paper reveals that multi‑task models suffer performance drops because tasks compete for the same internal subspace, and introduces Essential Subspace Merging (ESM) which separates critical directions and uses Polarized Scaling to keep multiple abilities stable, achieving significantly lower degradation than traditional baselines.

ESDESMModel Merging
0 likes · 16 min read
Model Ability Gets Squeezed Out in Multi‑Task Learning—How ESM Preserves It (CVPR 2026)
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Nov 3, 2025 · Artificial Intelligence

Smol Training Playbook: Secrets to Building World-Class LLMs

The article details the SmolLM3 3B‑parameter model, its architecture, dual‑mode inference, a three‑stage data‑curation strategy, rigorous ablation methods, preference optimisation (APO/DPO), model merging, and practical training‑stability tricks, offering a comprehensive guide for building high‑performing large language models.

APOLLM trainingModel Merging
0 likes · 13 min read
Smol Training Playbook: Secrets to Building World-Class LLMs