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Collections including paper arxiv:2508.20453

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 16 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

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

Paper • 2508.20453 • Published Aug 28 • 63

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

Paper • 2508.20453 • Published Aug 28 • 63

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

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

Paper • 2509.24002 • Published Sep 28 • 173
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools

Paper • 2510.19286 • Published Oct 22 • 8
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43

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

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

Paper • 2508.05748 • Published Aug 7 • 141
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28 • 63

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 • 30
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 33
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review

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

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

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

Paper • 2508.14704 • Published Aug 20 • 43

Provable Benefits of In-Tool Learning for Large Language Models

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

Paper • 2508.20453 • Published Aug 28 • 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 • 15
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10 • 56

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

Paper • 2508.20453 • Published Aug 28 • 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 • 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 • 63

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 16 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

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 • 30
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 33
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

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

Paper • 2508.20453 • Published Aug 28 • 63

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review

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

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

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

Paper • 2508.14704 • Published Aug 20 • 43

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

Paper • 2508.20453 • Published Aug 28 • 63

Provable Benefits of In-Tool Learning for Large Language Models

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

Paper • 2508.20453 • Published Aug 28 • 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 • 15
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Paper • 2509.08755 • Published Sep 10 • 56

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

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

Paper • 2509.24002 • Published Sep 28 • 173
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools

Paper • 2510.19286 • Published Oct 22 • 8
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43

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

Paper • 2508.20453 • Published Aug 28 • 63

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

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

Paper • 2508.05748 • Published Aug 7 • 141
MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Paper • 2508.20453 • Published Aug 28 • 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 • 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 • 63

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