TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Xiaosong, Chen, Ke, Dai, Xindi, Liang, Di, Peng, Minlong, Pang, Wei, Giunchiglia, Fausto, Feng, Xiaoyue, Liu, Yonghao, Guan, Renchu |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Dual-level Mixup for Graph Few-shot Learning with Fewer Tasks
by: Liu, Yonghao, et al.
Published: (2025)
by: Liu, Yonghao, et al.
Published: (2025)
Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive Learning
by: Liu, Yonghao, et al.
Published: (2025)
by: Liu, Yonghao, et al.
Published: (2025)
Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion
by: Liu, Yonghao, et al.
Published: (2026)
by: Liu, Yonghao, et al.
Published: (2026)
Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport
by: Liu, Yonghao, et al.
Published: (2025)
by: Liu, Yonghao, et al.
Published: (2025)
A Simple Graph Contrastive Learning Framework for Short Text Classification
by: Liu, Yonghao, et al.
Published: (2025)
by: Liu, Yonghao, et al.
Published: (2025)
Simple-Sampling and Hard-Mixup with Prototypes to Rebalance Contrastive Learning for Text Classification
by: Li, Mengyu, et al.
Published: (2024)
by: Li, Mengyu, et al.
Published: (2024)
Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration
by: Liu, Yonghao, et al.
Published: (2025)
by: Liu, Yonghao, et al.
Published: (2025)
Hypergraph Contrastive Learning for both Homophilic and Heterophilic Hypergraphs
by: Guan, Renchu, et al.
Published: (2025)
by: Guan, Renchu, et al.
Published: (2025)
Advancing Graph Few-Shot Learning via In-Context Learning
by: Guan, Renchu, et al.
Published: (2026)
by: Guan, Renchu, et al.
Published: (2026)
Resolving Word Vagueness with Scenario-guided Adapter for Natural Language Inference
by: Liu, Yonghao, et al.
Published: (2024)
by: Liu, Yonghao, et al.
Published: (2024)
Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training
by: Liu, Yonghao, et al.
Published: (2024)
by: Liu, Yonghao, et al.
Published: (2024)
Not All Parameters Are Created Equal: Smart Isolation Boosts Fine-Tuning Performance
by: Wang, Yao, et al.
Published: (2025)
by: Wang, Yao, et al.
Published: (2025)
Big-Thick Data generation via reference and personal context unification
by: Giunchiglia, Fausto, et al.
Published: (2024)
by: Giunchiglia, Fausto, et al.
Published: (2024)
KAE: A Property-based Method for Knowledge Graph Alignment and Extension
by: Shi, Daqian, et al.
Published: (2024)
by: Shi, Daqian, et al.
Published: (2024)
Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning
by: Lin, Zekai, et al.
Published: (2026)
by: Lin, Zekai, et al.
Published: (2026)
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
by: Du, Zhekai, et al.
Published: (2025)
by: Du, Zhekai, et al.
Published: (2025)
From Knowledge Representation to Knowledge Organization and Back
by: Giunchiglia, Fausto, et al.
Published: (2023)
by: Giunchiglia, Fausto, et al.
Published: (2023)
Crowdsourcing of Real-world Image Annotation via Visual Properties
by: Diao, Xiaolei, et al.
Published: (2026)
by: Diao, Xiaolei, et al.
Published: (2026)
Understanding Gen Alpha Digital Language: Evaluation of LLM Safety Systems for Content Moderation
by: Mehta, Manisha, et al.
Published: (2025)
by: Mehta, Manisha, et al.
Published: (2025)
What can Computer Vision learn from Ranganathan?
by: Bagchi, Mayukh, et al.
Published: (2026)
by: Bagchi, Mayukh, et al.
Published: (2026)
Task-Specific Directions: Definition, Exploration, and Utilization in Parameter Efficient Fine-Tuning
by: Si, Chongjie, et al.
Published: (2024)
by: Si, Chongjie, et al.
Published: (2024)
Continual Fine-Tuning with Provably Accurate and Parameter-Free Task Retrieval
by: Le, Hang Thi-Thuy, et al.
Published: (2026)
by: Le, Hang Thi-Thuy, et al.
Published: (2026)
DPI: Exploiting Parameter Heterogeneity for Interference-Free Fine-Tuning
by: Liu, Xiaoyu, et al.
Published: (2026)
by: Liu, Xiaoyu, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning With Adapters
by: Chen, Keyu, et al.
Published: (2024)
by: Chen, Keyu, et al.
Published: (2024)
UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter-Efficient Fine-Tuning of Large Models
by: Zhang, Xueyan, et al.
Published: (2025)
by: Zhang, Xueyan, et al.
Published: (2025)
Implicit Federated In-context Learning For Task-Specific LLM Fine-Tuning
by: Li, Dongcheng, et al.
Published: (2025)
by: Li, Dongcheng, et al.
Published: (2025)
TRACE: Task-Aware Adaptive Self-Evolving Agentic Jailbreaking
by: Zeng, Churui, et al.
Published: (2026)
by: Zeng, Churui, et al.
Published: (2026)
Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning
by: Yu, Feng, et al.
Published: (2025)
by: Yu, Feng, et al.
Published: (2025)
KoRe: Compact Knowledge Representations for Large Language Models
by: Cavicchini, Davide, et al.
Published: (2026)
by: Cavicchini, Davide, et al.
Published: (2026)
From Knowledge Organization to Knowledge Representation and Back
by: Giunchiglia, Fausto, et al.
Published: (2024)
by: Giunchiglia, Fausto, et al.
Published: (2024)
What Impacts the Quality of the User Answers when Asked about the Current Context?
by: Bison, Ivano, et al.
Published: (2024)
by: Bison, Ivano, et al.
Published: (2024)
Task-Aware Parameter-Efficient Fine-Tuning of Large Pre-Trained Models at the Edge
by: Hu, Senkang, et al.
Published: (2025)
by: Hu, Senkang, et al.
Published: (2025)
AnyTaskTune: Advanced Domain-Specific Solutions through Task-Fine-Tuning
by: Cui, Jiaxi, et al.
Published: (2024)
by: Cui, Jiaxi, et al.
Published: (2024)
Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models
by: Liao, Xiaoxuan, et al.
Published: (2025)
by: Liao, Xiaoxuan, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
by: Liu, Jingren, et al.
Published: (2024)
by: Liu, Jingren, et al.
Published: (2024)
Parameter-Efficient Multi-Task Fine-Tuning in Code-Related Tasks
by: Haque, Md Zahidul, et al.
Published: (2026)
by: Haque, Md Zahidul, et al.
Published: (2026)
Parameter-Efficient Multi-Task Learning via Progressive Task-Specific Adaptation
by: Gangwar, Neeraj, et al.
Published: (2025)
by: Gangwar, Neeraj, et al.
Published: (2025)
A Step Toward ESIPT‐Based Mitochondrial Probe That Responds to ATP Level
by: Yonghao Li, et al.
Published: (2024)
by: Yonghao Li, et al.
Published: (2024)
QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models
by: Jeon, Hyesung, et al.
Published: (2025)
by: Jeon, Hyesung, et al.
Published: (2025)
CoPEFT: Fast Adaptation Framework for Multi-Agent Collaborative Perception with Parameter-Efficient Fine-Tuning
by: Wei, Quanmin, et al.
Published: (2025)
by: Wei, Quanmin, et al.
Published: (2025)
Similar Items
-
Dual-level Mixup for Graph Few-shot Learning with Fewer Tasks
by: Liu, Yonghao, et al.
Published: (2025) -
Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive Learning
by: Liu, Yonghao, et al.
Published: (2025) -
Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion
by: Liu, Yonghao, et al.
Published: (2026) -
Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport
by: Liu, Yonghao, et al.
Published: (2025) -
A Simple Graph Contrastive Learning Framework for Short Text Classification
by: Liu, Yonghao, et al.
Published: (2025)