Copertina

Meta-Tool: Efficient Few-Shot Tool Adaptation for Small Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Kumar, Sachin
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MetaTool: Facilitating Large Language Models to Master Tools with Meta-task Augmentation
di: Wang, Xiaohan, et al.
Pubblicazione: (2024)

Few-Shot Recalibration of Language Models
di: Li, Xiang Lisa, et al.
Pubblicazione: (2024)

Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
di: Xu, Zhuoyan, et al.
Pubblicazione: (2024)

Meta-Semantics Augmented Few-Shot Relational Learning
di: Wu, Han, et al.
Pubblicazione: (2025)

Large Language Models as Tool Makers
di: Cai, Tianle, et al.
Pubblicazione: (2023)

PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation
di: Park, Junho, et al.
Pubblicazione: (2026)

Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation
di: Zhu, Dongsheng, et al.
Pubblicazione: (2025)

ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
di: Lin, Yujie, et al.
Pubblicazione: (2026)

Group Preference Optimization: Few-Shot Alignment of Large Language Models
di: Zhao, Siyan, et al.
Pubblicazione: (2023)

ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
di: Su, Hongjin, et al.
Pubblicazione: (2025)

BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation
di: Zhu, Alan, et al.
Pubblicazione: (2025)

Few-Shot Cross-Lingual Transfer for Prompting Large Language Models in Low-Resource Languages
di: Toukmaji, Christopher
Pubblicazione: (2024)

Tool Unlearning for Tool-Augmented LLMs
di: Cheng, Jiali, et al.
Pubblicazione: (2025)

Tool Learning with Foundation Models
di: Qin, Yujia, et al.
Pubblicazione: (2023)

Model-diff: A Tool for Comparative Study of Language Models in the Input Space
di: Liu, Weitang, et al.
Pubblicazione: (2024)

Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models
di: Luo, Zheng, et al.
Pubblicazione: (2026)

ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool Learning
di: Zeng, Xingshan, et al.
Pubblicazione: (2025)

Efficient and Scalable Estimation of Tool Representations in Vector Space
di: Moon, Suhong, et al.
Pubblicazione: (2024)

Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language Models
di: Ozyurt, Yilmazcan, et al.
Pubblicazione: (2023)

GRAD: Generative Retrieval-Aligned Demonstration Sampler for Efficient Few-Shot Reasoning
di: Gabouj, Oussama, et al.
Pubblicazione: (2025)

Tools Fail: Detecting Silent Errors in Faulty Tools
di: Sun, Jimin, et al.
Pubblicazione: (2024)

ToolRL: Reward is All Tool Learning Needs
di: Qian, Cheng, et al.
Pubblicazione: (2025)

MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification
di: Zeng, Xia, et al.
Pubblicazione: (2024)

Leveraging Zero-Shot Prompting for Efficient Language Model Distillation
di: Vöge, Lukas, et al.
Pubblicazione: (2024)

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization
di: Wang, Haozhe, et al.
Pubblicazione: (2025)

LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model
di: Jiang, Haitao, et al.
Pubblicazione: (2023)

Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models
di: Golchin, Shahriar, et al.
Pubblicazione: (2023)

LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanations
di: Wang, Qianli, et al.
Pubblicazione: (2024)

LoopTool: Closing the Data-Training Loop for Robust LLM Tool Calls
di: Zhang, Kangning, et al.
Pubblicazione: (2025)

Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare
di: Gondara, Lovedeep, et al.
Pubblicazione: (2025)

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
di: Chen, Sijia, et al.
Pubblicazione: (2024)

AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent
di: Luo, Haipeng, et al.
Pubblicazione: (2025)

Tool Calling is Linearly Readable and Steerable in Language Models
di: Wu, Zekun, et al.
Pubblicazione: (2026)

Tool-Star: Empowering LLM-Brained Multi-Tool Reasoner via Reinforcement Learning
di: Dong, Guanting, et al.
Pubblicazione: (2025)

iTool: Reinforced Fine-Tuning with Dynamic Deficiency Calibration for Advanced Tool Use
di: Zeng, Yirong, et al.
Pubblicazione: (2025)

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
di: Wang, Xingyao, et al.
Pubblicazione: (2023)

Manual Verbalizer Enrichment for Few-Shot Text Classification
di: Nguyen, Quang Anh, et al.
Pubblicazione: (2024)

Emergent Communication Pretraining for Few-Shot Machine Translation
di: Li, Yaoyiran, et al.
Pubblicazione: (2020)

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
di: Zheng, Xiaosen, et al.
Pubblicazione: (2024)

Meta-Adaptive Prompt Distillation for Few-Shot Visual Question Answering
di: Gupta, Akash, et al.
Pubblicazione: (2025)