Cover Image

Self-Training Large Language Models for Tool-Use Without Demonstrations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luo, Ne, Gema, Aryo Pradipta, He, Xuanli, van Krieken, Emile, Lesci, Pietro, Minervini, Pasquale
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lost in Time: Clock and Calendar Understanding Challenges in Multimodal LLMs
by: Saxena, Rohit, et al.
Published: (2025)

Edinburgh Clinical NLP at MEDIQA-CORR 2024: Guiding Large Language Models with Hints
by: Gema, Aryo Pradipta, et al.
Published: (2024)

Analysing the Residual Stream of Language Models Under Knowledge Conflicts
by: Zhao, Yu, et al.
Published: (2024)

SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks
by: Kwan, Wai-Chung, et al.
Published: (2026)

Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4
by: Gema, Aryo Pradipta, et al.
Published: (2024)

The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
by: Hong, Giwon, et al.
Published: (2024)

Noiser: Bounded Input Perturbations for Attributing Large Language Models
by: Madani, Mohammad Reza Ghasemi, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain
by: Gema, Aryo Pradipta, et al.
Published: (2023)

Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering
by: Zhao, Yu, et al.
Published: (2024)

Mixtures of In-Context Learners
by: Hong, Giwon, et al.
Published: (2024)

PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
by: Leang, Joshua Ong Jun, et al.
Published: (2025)

Are We Done with MMLU?
by: Gema, Aryo Pradipta, et al.
Published: (2024)

DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations
by: Gema, Aryo Pradipta, et al.
Published: (2024)

An Analysis of Decoding Methods for LLM-based Agents for Faithful Multi-Hop Question Answering
by: Murphy, Alexander, et al.
Published: (2025)

Using Natural Language Explanations to Improve Robustness of In-context Learning
by: He, Xuanli, et al.
Published: (2023)

GRADA: Graph-based Reranking against Adversarial Documents Attack
by: Zheng, Jingjie, et al.
Published: (2025)

CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning
by: Leang, Joshua Ong Jun, et al.
Published: (2024)

Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them
by: Rajani, Neel, et al.
Published: (2025)

Neurosymbolic Diffusion Models
by: van Krieken, Emile, et al.
Published: (2025)

Do Composed Image Retrieval Benchmarks Require Multimodal Composition?
by: Attimonelli, Matteo, et al.
Published: (2026)

Neurosymbolic Reasoning Shortcuts under the Independence Assumption
by: van Krieken, Emile, et al.
Published: (2025)

AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets
by: Lesci, Pietro, et al.
Published: (2024)

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
by: Tyukin, Georgy, et al.
Published: (2024)

TuBA: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning
by: He, Xuanli, et al.
Published: (2024)

On the Independence Assumption in Neurosymbolic Learning
by: van Krieken, Emile, et al.
Published: (2024)

Tending Towards Stability: Convergence Challenges in Small Language Models
by: Martinez, Richard Diehl, et al.
Published: (2024)

Analysing The Impact of Sequence Composition on Language Model Pre-Training
by: Zhao, Yu, et al.
Published: (2024)

A Comparative Study on Patient Language across Therapeutic Domains for Effective Patient Voice Classification in Online Health Discussions
by: Lysandrou, Giorgos, et al.
Published: (2024)

Inverse Scaling in Test-Time Compute
by: Gema, Aryo Pradipta, et al.
Published: (2025)

Probing the Emergence of Cross-lingual Alignment during LLM Training
by: Wang, Hetong, et al.
Published: (2024)

FairBelief -- Assessing Harmful Beliefs in Language Models
by: Setzu, Mattia, et al.
Published: (2024)

Can GPT-3.5 Generate and Code Discharge Summaries?
by: Falis, Matúš, et al.
Published: (2024)

Answerability in Retrieval-Augmented Open-Domain Question Answering
by: Abdumalikov, Rustam, et al.
Published: (2024)

PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs
by: van der Wal, Oskar, et al.
Published: (2025)

Agentic Tool Use in Large Language Models
by: Hu, Jinchao, et al.
Published: (2026)

What Language is This? Ask Your Tokenizer
by: Meister, Clara, et al.
Published: (2026)

An Auditing Test To Detect Behavioral Shift in Language Models
by: Richter, Leo, et al.
Published: (2024)

Enhancing Long Document Long Form Summarisation with Self-Planning
by: Du, Xiaotang, et al.
Published: (2025)

Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models
by: He, Wei, et al.
Published: (2024)

Attacks on Third-Party APIs of Large Language Models
by: Zhao, Wanru, et al.
Published: (2024)