:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gao, Xin, Zhang, Ruiyi, Du, Meixi, Qin, Peijia, Xie, Pengtao
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2605.05758
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation
by: Qin, Peijia, et al.
Published: (2024)

DreamPRM-Code: Function-as-Step Process Reward Model with Label Correction for LLM Coding
by: Zhang, Ruiyi, et al.
Published: (2025)

BiLoRA: A Bi-level Optimization Framework for Overfitting-Resilient Low-Rank Adaptation of Large Pre-trained Models
by: Qiang, Rushi, et al.
Published: (2024)

SteganoBackdoor: Stealthy and Data-Efficient Backdoor Attacks on Language Models
by: Xue, Eric, et al.
Published: (2025)

Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning
by: Hu, Bokai, et al.
Published: (2024)

ToolRM: Outcome Reward Models for Tool-Calling Large Language Models
by: Agarwal, Mayank, et al.
Published: (2025)

TOOL-ED: Enhancing Empathetic Response Generation with the Tool Calling Capability of LLM
by: Cao, Huiying, et al.
Published: (2024)

Can Prompts Rewind Time for LLMs? Evaluating the Effectiveness of Prompted Knowledge Cutoffs
by: Gao, Xin, et al.
Published: (2025)

Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models
by: Huang, Zhongzhen, et al.
Published: (2024)

Alignment for Efficient Tool Calling of Large Language Models
by: Xu, Hongshen, et al.
Published: (2025)

CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios
by: Huang, Shiting, et al.
Published: (2025)

DAJ: Data-Reweighted LLM Judge for Test-Time Scaling in Code Generation
by: Qin, Peijia, et al.
Published: (2026)

T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step
by: Chen, Zehui, et al.
Published: (2023)

Natural Language Tools: A Natural Language Approach to Tool Calling In Large Language Agents
by: Johnson, Reid T., et al.
Published: (2025)

AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
by: Du, Yu, et al.
Published: (2024)

AIBuildAI: An AI Agent for Automatically Building AI Models
by: Zhang, Ruiyi, et al.
Published: (2026)

ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios
by: Ye, Junjie, et al.
Published: (2024)

NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models
by: Han, Han, et al.
Published: (2024)

FunPRM: Function-as-Step Process Reward Model with Meta Reward Correction for Code Generation
by: Zhang, Ruiyi, et al.
Published: (2026)

Defense against Prompt Injection Attacks via Mixture of Encodings
by: Zhang, Ruiyi, et al.
Published: (2025)

EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis
by: Liu, Zhiwei, et al.
Published: (2024)

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

Task-Aligned Tool Recommendation for Large Language Models
by: Gao, Hang, et al.
Published: (2024)

ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph
by: Liu, Xukun, et al.
Published: (2024)

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

ToolMem: Enhancing Multimodal Agents with Learnable Tool Capability Memory
by: Xiao, Yunzhong, et al.
Published: (2025)

AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning
by: Zhang, Ruiyi, et al.
Published: (2024)

The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration
by: Xu, Haoyuan, et al.
Published: (2026)

ToolSpec: Accelerating Tool Calling via Schema-Aware and Retrieval-Augmented Speculative Decoding
by: Xia, Heming, et al.
Published: (2026)

ToolBridge: An Open-Source Dataset to Equip LLMs with External Tool Capabilities
by: Jin, Zhenchao, et al.
Published: (2024)

When2Call: When (not) to Call Tools
by: Ross, Hayley, et al.
Published: (2025)

Enhancing Tool Calling in LLMs with the International Tool Calling Dataset
by: Zhang, Zuoyu, et al.
Published: (2026)

StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models
by: Guo, Zhicheng, et al.
Published: (2024)

ToolFlow: Boosting LLM Tool-Calling Through Natural and Coherent Dialogue Synthesis
by: Wang, Zezhong, et al.
Published: (2024)

Learning Evolving Tools for Large Language Models
by: Chen, Guoxin, et al.
Published: (2024)

ToolGrad: Efficient Tool-use Dataset Generation with Textual "Gradients"
by: Zhou, Zhongyi, et al.
Published: (2025)

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

BioMedJImpact: A Comprehensive Dataset and LLM Pipeline for AI Engagement and Scientific Impact Analysis of Biomedical Journals
by: Wang, Ruiyu, et al.
Published: (2025)

Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc Reasoning
by: Cao, Qi, et al.
Published: (2026)

ToolCoder: A Systematic Code-Empowered Tool Learning Framework for Large Language Models
by: Ding, Hanxing, et al.
Published: (2025)