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Collections including paper arxiv:2509.09734

Foundational & Modern AI Research (Curated)

A curated selection of foundational and modern AI research papers that meaningfully influence how real-world AI systems are designed, evaluated, and g

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 121
Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 10
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT

Paper • 2210.04186 • Published Oct 9, 2022

mahoney-context-protocol

AgentOrchestra: A Hierarchical Multi-Agent Framework for General-Purpose Task Solving

Paper • 2506.12508 • Published Jun 14, 2025 • 1
Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling

Paper • 2507.23370 • Published Jul 31, 2025
MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools

Paper • 2509.09734 • Published Sep 10, 2025 • 16
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?

Paper • 2508.01780 • Published Aug 3, 2025 • 21

Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations

Paper • 2508.09789 • Published Aug 13, 2025 • 5
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents

Paper • 2508.13186 • Published Aug 14, 2025 • 20
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents

Paper • 2508.04038 • Published Aug 6, 2025 • 1
Prompt Orchestration Markup Language

Paper • 2508.13948 • Published Aug 19, 2025 • 48

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review

Paper • 2504.19678 • Published Apr 28, 2025 • 3
Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

Paper • 2503.23278 • Published Mar 30, 2025 • 1
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20, 2025 • 43

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

Paper • 2508.15760 • Published Aug 21, 2025 • 47
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?

Paper • 2508.01780 • Published Aug 3, 2025 • 21
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs

Paper • 2304.08244 • Published Apr 14, 2023 • 1
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22, 2025 • 162

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Paper • 2402.15506 • Published Feb 23, 2024 • 18
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 34
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

Foundational & Modern AI Research (Curated)

A curated selection of foundational and modern AI research papers that meaningfully influence how real-world AI systems are designed, evaluated, and g

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 121
Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 10
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT

Paper • 2210.04186 • Published Oct 9, 2022

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review

Paper • 2504.19678 • Published Apr 28, 2025 • 3
Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

Paper • 2503.23278 • Published Mar 30, 2025 • 1
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20, 2025 • 43

mahoney-context-protocol

AgentOrchestra: A Hierarchical Multi-Agent Framework for General-Purpose Task Solving

Paper • 2506.12508 • Published Jun 14, 2025 • 1
Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling

Paper • 2507.23370 • Published Jul 31, 2025
MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools

Paper • 2509.09734 • Published Sep 10, 2025 • 16
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?

Paper • 2508.01780 • Published Aug 3, 2025 • 21

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

Paper • 2508.15760 • Published Aug 21, 2025 • 47
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?

Paper • 2508.01780 • Published Aug 3, 2025 • 21
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs

Paper • 2304.08244 • Published Apr 14, 2023 • 1
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22, 2025 • 162

Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations

Paper • 2508.09789 • Published Aug 13, 2025 • 5
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents

Paper • 2508.13186 • Published Aug 14, 2025 • 20
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents

Paper • 2508.04038 • Published Aug 6, 2025 • 1
Prompt Orchestration Markup Language

Paper • 2508.13948 • Published Aug 19, 2025 • 48

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Paper • 2402.15506 • Published Feb 23, 2024 • 18
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 34
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

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