NEW Articles from Team or Enterprise organizations will get promoted to the main section. Building and evaluating Multimodal Rerankers
UlrickBL
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📌 Rethinking Multimodality from an Industry Perspective: Captioning Is Far More Important Than You Think
Borise
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<h1> Getting Devs to Change Their Workflow Requires Being 10x Better, Not 2x Better</h1>
mambaCodes
• • 1
🛡️ Safeguarding AI: Building Falconz as an MCP Server for Enterprise LLM Security
Xhaheen
• • 1
BERTs that chat: turn any BERT into a chatbot with dLLM
OnAnOrange
• • 4
SARLO-80: Worldwide Slant SAR Language Optic Dataset at 80 cm Resolution
SoleneDEBUYSERE
• • 5
September(2025) LLM Scientific & Specialized Benchmarks Report [Foresight Analysis] By (AIPRL-LIR) AI Parivartan Research Lab(AIPRL)-LLMs Intelligence Report
rajkumarrawal
• • 1
How MCP Blockly Makes MCP Server Creation Accessible for Everyone
MCP-1st-Birthday
• • 9
🛡️ Global Compliance Audit MCP Server: Enterprise Compliance Made Simple
MCP-1st-Birthday
• • 1
各家AI划地盘:你以为的公开数据,其实被"圈地"了
VirtualOasis
• • 3
Building Jobly: Semantic Job Matching with RAG and Vector Embeddings
MCP-1st-Birthday
• • 12
Z-Image vs FLUX.1 (Flux 2): Which AI Model Rules in 2025?
azhan77168
• • 4
Use our radar dataset
InezCornell
• AutoBench Run 4 is out with Gemini 3 Pro, Gpt 5.1, Grok 4.1 etc. And the winner is not who you expect.
PeterKruger
• • 1
Gemini-3 Benchmarkathon
joelniklaus
• • 10
Building a Complete AI Agent Evaluation Ecosystem: From Instrumentation to Intelligence
MCP-1st-Birthday
• • 4
Breaking Language Barriers: How Synthetic Speech Can Revolutionize Multilingual ASR Training
nprak26
• • 1
WorkflowDrivenAgent: A Novel Paradigm for Deterministic Multi-Agent AI Systems
darielnoel
• 本周最值得关注的论文TOP10|11.27
Miracleplus01
• Curating datasets directly on the Hub
dvilasuero
• • 22