Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

2,364 searchable experts 2,966 tracked across all sources
Clear
Showing signals surfaced by Tom Aarsen ×
Debated

The questions experts are actively pulling apart

One card per development. Sources are clustered; expert reactions remain attributable.

Established AI field signal Resource 15d ago
V-SPLADE document retrieval models release

V-SPLADE Quality Document Retrieval - a Hugging Face Space by hugging-apps

3 experts are actively discussing the implications.

1 expert 1 community 1 sources clustered
Tom Aarsen

“The free space, no login needed: huggingface.co/spaces/huggi...”

3 experts discussed this · 13 posts
Tom Aarsen: NAVER, the original authors of SPLADE, just published V-SPLADE, an inference-free sparse retriever for visual document retrieval. Two models on the same backbone (ModernVBERT, 250M params), both Ap…
Tom Aarsen: Quality: huggingface.co/naver/v-spla... 🧵
Tom Aarsen: Efficient: huggingface.co/naver/v-spla... 🧵
Open the full discussion →
Primary source huggingface.co ↗
Established AI field signal Resource 9d ago
Tencent R3 rerank embedding models

tencent/R3-rerank-0.6b · Hugging Face

2 experts are actively discussing the implications.

1 expert 1 community 1 sources clustered
Tom Aarsen

“The reranker: huggingface.co/tencent/R3-r...”

2 experts discussed this · 8 posts
Tom Aarsen: Tencent just published R3-Skill, a two-stage retrieval stack purpose-built for a problem RAG-style retrievers weren't designed for: routing LLM agent skills (think Anthropic's SKILLmd format). Two …
Tom Aarsen: The embedding model: huggingface.co/tencent/R3-e...
Tom Aarsen: The reranker: huggingface.co/tencent/R3-r...
Open the full discussion →
Primary source huggingface.co ↗