arXiv AI By Andrea Ferrario

Tree-Based Formalization of Multi-Agent Complementarity in Human-AI Interactions

Read the original on arXiv AI →

arXiv:2606. 04779v1 Announce Type: new Abstract: Complementarity is the case in which a human--AI interaction (HAI) outperforms the best prediction benchmark available among its members.

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arXiv Machine Learning
Aug 18

The Limits of Binding in Dual Encoders

arXiv:2608. 15971v1 Announce Type: new Abstract: Dual-encoder models such as CLIP score an image-caption pair by a single inner product of two independently computed unit vectors, and fail at binding, often scoring near chance when asked to distinguish "a red car and a blue dog" from "a blue car and a red dog".

By Kin Ian Lo
Hugging Face Trending Papers
Aug 5

Computationally Efficient Collaborative Communication Via Regularity-Based Coarsening

Our results show that the existence of a short high-utility protocol already suffices for efficient communication. In particular, in a game with $n$ possible observations and $m$ actions: (1) For any achievable target utility $α$, we give an algorithm with $\mathrm{poly}(n, m, 1/ε)$ runtime that designs a protocol achieving utility at least $α-ε$ using only $2^{\mathcal O(CC_α(G))}/ε^2$ bits of communication.