CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
Fuente:
arXiv
Saved in:
| Main Authors: | Yuan, Lifan, Chen, Yangyi, Wang, Xingyao, Fung, Yi R., Peng, Hao, Ji, Heng |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Examining LLMs' Uncertainty Expression Towards Questions Outside Parametric Knowledge
by: Liu, Genglin, et al.
Published: (2023)
by: Liu, Genglin, et al.
Published: (2023)
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
by: Wang, Xingyao, et al.
Published: (2023)
by: Wang, Xingyao, et al.
Published: (2023)
Executable Code Actions Elicit Better LLM Agents
by: Wang, Xingyao, et al.
Published: (2024)
by: Wang, Xingyao, et al.
Published: (2024)
SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
by: Xu, Tianyang, et al.
Published: (2024)
by: Xu, Tianyang, et al.
Published: (2024)
Scaling Laws for Predicting Downstream Performance in LLMs
by: Chen, Yangyi, et al.
Published: (2024)
by: Chen, Yangyi, et al.
Published: (2024)
DeepAgent: A General Reasoning Agent with Scalable Toolsets
by: Li, Xiaoxi, et al.
Published: (2025)
by: Li, Xiaoxi, et al.
Published: (2025)
SOLO: A Single Transformer for Scalable Vision-Language Modeling
by: Chen, Yangyi, et al.
Published: (2024)
by: Chen, Yangyi, et al.
Published: (2024)
CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation
by: Ziegler, Ingo, et al.
Published: (2024)
by: Ziegler, Ingo, et al.
Published: (2024)
Advancing LLM Reasoning Generalists with Preference Trees
by: Yuan, Lifan, et al.
Published: (2024)
by: Yuan, Lifan, et al.
Published: (2024)
RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
by: Liu, Wanlong, et al.
Published: (2024)
by: Liu, Wanlong, et al.
Published: (2024)
A Comparative Study of Specialized LLMs as Dense Retrievers
by: Zhang, Hengran, et al.
Published: (2025)
by: Zhang, Hengran, et al.
Published: (2025)
A Rubric-Supervised Critic from Sparse Real-World Outcomes
by: Wang, Xingyao, et al.
Published: (2026)
by: Wang, Xingyao, et al.
Published: (2026)
Retrieval Augmented Question Answering: When Should LLMs Admit Ignorance?
by: Wang, Dingmin, et al.
Published: (2025)
by: Wang, Dingmin, et al.
Published: (2025)
Word Embeddings Are Steers for Language Models
by: Han, Chi, et al.
Published: (2023)
by: Han, Chi, et al.
Published: (2023)
Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
by: Mukherjee, Sagnik, et al.
Published: (2026)
by: Mukherjee, Sagnik, et al.
Published: (2026)
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
by: Chen, Zui, et al.
Published: (2024)
by: Chen, Zui, et al.
Published: (2024)
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
by: Shen, Junhong, et al.
Published: (2024)
by: Shen, Junhong, et al.
Published: (2024)
ModelingAgent: Bridging LLMs and Mathematical Modeling for Real-World Challenges
by: Qian, Cheng, et al.
Published: (2025)
by: Qian, Cheng, et al.
Published: (2025)
Scalable Token-Level Hallucination Detection in Large Language Models
by: Min, Rui, et al.
Published: (2026)
by: Min, Rui, et al.
Published: (2026)
LeTI: Learning to Generate from Textual Interactions
by: Wang, Xingyao, et al.
Published: (2023)
by: Wang, Xingyao, et al.
Published: (2023)
Towards Data-efficient Customer Intent Recognition with Prompt-based Learning Paradigm
by: Luo, Hengyu, et al.
Published: (2023)
by: Luo, Hengyu, et al.
Published: (2023)
Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs
by: Ovadia, Oded, et al.
Published: (2023)
by: Ovadia, Oded, et al.
Published: (2023)
Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority
by: Shen, Zhanming, et al.
Published: (2026)
by: Shen, Zhanming, et al.
Published: (2026)
Model Extrapolation Expedites Alignment
by: Zheng, Chujie, et al.
Published: (2024)
by: Zheng, Chujie, et al.
Published: (2024)
DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
by: Xiao, Yongkang, et al.
Published: (2025)
by: Xiao, Yongkang, et al.
Published: (2025)
RLPR: Extrapolating RLVR to General Domains without Verifiers
by: Yu, Tianyu, et al.
Published: (2025)
by: Yu, Tianyu, et al.
Published: (2025)
RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation
by: Xu, Ran, et al.
Published: (2025)
by: Xu, Ran, et al.
Published: (2025)
Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation
by: Yang, Zhuolin, et al.
Published: (2026)
by: Yang, Zhuolin, et al.
Published: (2026)
SyncMind: Measuring Agent Out-of-Sync Recovery in Collaborative Software Engineering
by: Guo, Xuehang, et al.
Published: (2025)
by: Guo, Xuehang, et al.
Published: (2025)
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
by: Agarwal, Shivam, et al.
Published: (2025)
by: Agarwal, Shivam, et al.
Published: (2025)
Incremental Summarization for Customer Support via Progressive Note-Taking and Agent Feedback
by: Wu, Yisha, et al.
Published: (2025)
by: Wu, Yisha, et al.
Published: (2025)
Entropy Centroids as Intrinsic Rewards for Test-Time Scaling
by: Zhao, Wenshuo, et al.
Published: (2026)
by: Zhao, Wenshuo, et al.
Published: (2026)
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
by: Cui, Ganqu, et al.
Published: (2025)
by: Cui, Ganqu, et al.
Published: (2025)
Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problem
by: Court, Sara, et al.
Published: (2024)
by: Court, Sara, et al.
Published: (2024)
Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training
by: Chen, Yangyi, et al.
Published: (2025)
by: Chen, Yangyi, et al.
Published: (2025)
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking
by: Liu, Zijun, et al.
Published: (2024)
by: Liu, Zijun, et al.
Published: (2024)
xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning
by: Qian, Cheng, et al.
Published: (2025)
by: Qian, Cheng, et al.
Published: (2025)
CauScientist: Teaching LLMs to Respect Data for Causal Discovery
by: Peng, Bo, et al.
Published: (2026)
by: Peng, Bo, et al.
Published: (2026)
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
by: Liu, Yijun, et al.
Published: (2024)
by: Liu, Yijun, et al.
Published: (2024)
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs
by: Zhang, Jintian, et al.
Published: (2024)
by: Zhang, Jintian, et al.
Published: (2024)
Similar Items
-
Examining LLMs' Uncertainty Expression Towards Questions Outside Parametric Knowledge
by: Liu, Genglin, et al.
Published: (2023) -
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
by: Wang, Xingyao, et al.
Published: (2023) -
Executable Code Actions Elicit Better LLM Agents
by: Wang, Xingyao, et al.
Published: (2024) -
SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
by: Xu, Tianyang, et al.
Published: (2024) -
Scaling Laws for Predicting Downstream Performance in LLMs
by: Chen, Yangyi, et al.
Published: (2024)