PDF Viewer

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $10K - $14K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (28)

[1]
LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora
2025Luyao Zhuang, Shengyuan Chen et al.
[2]
On the Self-awareness of Large Reasoning Models' Capability Boundaries
2025Qingjie Zhang, Yujia Fu et al.
[3]
Mol-R1: Towards Explicit Long-CoT Reasoning in Molecule Discovery
2025Jiatong Li, Weida Wang et al.
[4]
Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training
2025Tianqing Fang, Zhisong Zhang et al.
[5]
Tool-Star: Empowering LLM-Brained Multi-Tool Reasoner via Reinforcement Learning
2025Guanting Dong, Yifei Chen et al.
[6]
BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs
2025Junxiao Yang, Jinzhe Tu et al.
[7]
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
2025Bowen Jin, Hansi Zeng et al.
[8]
Enhancing LLM Reliability via Explicit Knowledge Boundary Modeling
2025Hang Zheng, Hongshen Xu et al.
[9]
Search-o1: Agentic Search-Enhanced Large Reasoning Models
2025Xiaoxi Li, Guanting Dong et al.
[10]
Sufficient Context: A New Lens on Retrieval Augmented Generation Systems
2024Hailey Joren, Jianyi Zhang et al.
[11]
RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards
2024Xinze Li, Senkun Mei et al.
[12]
Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals
2024Lida Chen, Zujie Liang et al.
[13]
Confidence Under the Hood: An Investigation into the Confidence-Probability Alignment in Large Language Models
2024Abhishek Kumar, Robert D Morabito et al.
[14]
FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
2024Jiajie Jin, Yutao Zhu et al.
[15]
Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
2024Hongshen Xu, Zichen Zhu et al.
[16]
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
2024Zhihong Shao, Peiyi Wang et al.
[17]
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
2023Akari Asai, Zeqiu Wu et al.
[18]
RA-DIT: Retrieval-Augmented Dual Instruction Tuning
2023Xi Victoria Lin, Xilun Chen et al.
[19]
Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness
2023Jiuhai Chen, Jonas Mueller
[20]
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
2023Katherine Tian, E. Mitchell et al.

Showing 20 of 28 references

Founder's Pitch

"Boundary-Aware Policy Optimization enhances reliability for LLM-driven agentic search by teaching AI to recognize its knowledge limits."

AgentsScore: 8View PDF ↗

Commercial Viability Breakdown

Breakdown pending for this paper.

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 1/16/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.