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Collections including paper arxiv:2508.20453

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

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence

Paper • 2511.18538 • Published Nov 23, 2025 • 304
Memory in the Age of AI Agents

Paper • 2512.13564 • Published Dec 15, 2025 • 157

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use

Paper • 2509.24002 • Published Sep 28, 2025 • 179
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools

Paper • 2510.19286 • Published Oct 22, 2025 • 9
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20, 2025 • 43

Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?

Paper • 2508.03644 • Published Aug 5, 2025 • 25
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent

Paper • 2508.05748 • Published Aug 7, 2025 • 142
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

a collection of algorithmic agents for user interfaces/interactions, program synthesis, and robotics

End-to-End Goal-Driven Web Navigation

Paper • 1602.02261 • Published Feb 6, 2016
Learning Language Games through Interaction

Paper • 1606.02447 • Published Jun 8, 2016
Naturalizing a Programming Language via Interactive Learning

Paper • 1704.06956 • Published Apr 23, 2017
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Paper • 1802.08802 • Published Feb 24, 2018 • 2

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

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28, 2025 • 11
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28, 2025 • 16
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10, 2025 • 56

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

Hammer: Robust Function-Calling for On-Device Language Models via Function Masking

Paper • 2410.04587 • Published Oct 6, 2024 • 2
TaskCraft: Automated Generation of Agentic Tasks

Paper • 2506.10055 • Published Jun 11, 2025 • 32
Direct Multi-Turn Preference Optimization for Language Agents

Paper • 2406.14868 • Published Jun 21, 2024
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

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

a collection of algorithmic agents for user interfaces/interactions, program synthesis, and robotics

End-to-End Goal-Driven Web Navigation

Paper • 1602.02261 • Published Feb 6, 2016
Learning Language Games through Interaction

Paper • 1606.02447 • Published Jun 8, 2016
Naturalizing a Programming Language via Interactive Learning

Paper • 1704.06956 • Published Apr 23, 2017
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Paper • 1802.08802 • Published Feb 24, 2018 • 2

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

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

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence

Paper • 2511.18538 • Published Nov 23, 2025 • 304
Memory in the Age of AI Agents

Paper • 2512.13564 • Published Dec 15, 2025 • 157

Provable Benefits of In-Tool Learning for Large Language Models

Paper • 2508.20755 • Published Aug 28, 2025 • 11
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on τ-bench

Paper • 2508.20931 • Published Aug 28, 2025 • 16
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10, 2025 • 56

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63
MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use

Paper • 2509.24002 • Published Sep 28, 2025 • 179
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools

Paper • 2510.19286 • Published Oct 22, 2025 • 9
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20, 2025 • 43

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?

Paper • 2508.03644 • Published Aug 5, 2025 • 25
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent

Paper • 2508.05748 • Published Aug 7, 2025 • 142
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

Hammer: Robust Function-Calling for On-Device Language Models via Function Masking

Paper • 2410.04587 • Published Oct 6, 2024 • 2
TaskCraft: Automated Generation of Agentic Tasks

Paper • 2506.10055 • Published Jun 11, 2025 • 32
Direct Multi-Turn Preference Optimization for Language Agents

Paper • 2406.14868 • Published Jun 21, 2024
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28, 2025 • 63

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