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.

2,397 searchable experts 4,280 tracked across all sources
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The developments commanding sustained expert attention

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New NLP & language Signal 19h ago
⚡ 8 h early

Rethinking Linguistic Tests for Large Language Models: Airplanes Aren't Birds | Northern European Journal of Language Technology

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Olivia Guest Baldur Bjarnason

“Glad more are realising this is a blunder! > By applying these tests outside their proper context [such as to LLM-based AI systems], the findings derived from such practice answer no real questions and fail to provide meaningful insights. doi.org/10.3384/ne…”

Primary source doi.org ↗
New NLP & language Signal 19h ago

Rethinking Linguistic Tests for Large Language Models: Airplanes Aren't Birds | Northern European Journal of Language Technology

2 directory members surfaced this signal.

2 experts 2 communities 1 sources clustered
Olivia Guest Baldur Bjarnason

“Glad more are realising this is a blunder! > By applying these tests outside their proper context [such as to LLM-based AI systems], the findings derived from such practice answer no real questions and fail to provide meaningful insights. doi.org/10.3384/ne…”

Primary source nejlt.ep.liu.se ↗
New NLP & language Signal 7h ago

NLData2Opt: Benchmarking Parameter Derivation and Prediction for Modeling Optimization Problems from Natural Language and Data

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered
arxiv cs.CL

“Lijia Liu, Kyohei Atarashi, Jiyi Li, Koh Takeuchi, Shunji Umetani, Hisashi Kashima NLData2Opt: Benchmarking Parameter Derivation and Prediction for Modeling Optimization Problems from Natural Language and Data https://arxiv.org/abs/2610.22889”

Primary source arxiv.org ↗