conftrace_

model merging

234 papers

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Co-occurring keywords

large language model (13587) transfer learning (5449) multi-task learning (2575) knowledge distillation (3725) model compression (3302) language model (4599) low-rank adaptation (560) parameter-efficient fine-tuning (736) domain adaptation (4595) task vector (25)

Papers

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint AACL 2025
Mergenetic: a Simple Evolutionary Model Merging Library ACL 2025
Parameter Competition Balancing for Model Merging NIPS 2024
AdaMerging: Adaptive Model Merging for Multi-Task Learning ICLR 2024
Chamain: Harmonizing Character Persona Integrity with Domain-Adaptive Knowledge in Dialogue Generation ACL 2024
DEM: Distribution Edited Model for Training with Mixed Data Distributions EMNLP 2024
Knowledge Fusion By Evolving Weights of Language Models ACL 2024
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts ACL 2024
LoRA-Flow: Dynamic LoRA Fusion for Large Language Models in Generative Tasks ACL 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models CVPR 2024
Reusing Transferable Weight Increments for Low-resource Style Generation EMNLP 2024
MetaGPT: Merging Large Language Models Using Model Exclusive Task Arithmetic EMNLP 2024
Amalgamating Multi-Task Models with Heterogeneous Architectures AAAI 2024
$\texttt{Model-GLUE}$: Democratized LLM Scaling for A Large Model Zoo in the Wild NIPS 2024
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning ACL 2024
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging NIPS 2024
DogeRM: Equipping Reward Models with Domain Knowledge through Model Merging EMNLP 2024
Scalable Data Ablation Approximations for Language Models through Modular Training and Merging EMNLP 2024
Arcee’s MergeKit: A Toolkit for Merging Large Language Models EMNLP 2024
Unlocking the Potential of Model Merging for Low-Resource Languages EMNLP 2024
SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models EMNLP 2024
Model Merging and Safety Alignment: One Bad Model Spoils the Bunch EMNLP 2024
Merge to Learn: Efficiently Adding Skills to Language Models with Model Merging EMNLP 2024
$C^2M^3$: Cycle-Consistent Multi-Model Merging NIPS 2024
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof NIPS 2024