Xeno-Interpretability: Investigating the Alien Minds of LLMs
arXiv:2609.20408v2 Announce Type: replace-cross Abstract: Large language models are usually interpreted through concepts that humans already possess: truthfulness, refusal, deception,…
by ODEFTO AI Labs
arXiv:2609.20408v2 Announce Type: replace-cross Abstract: Large language models are usually interpreted through concepts that humans already possess: truthfulness, refusal, deception,…
arXiv:2609.22161v1 Announce Type: new Abstract: Medical large language models are commonly trained on mixtures of didactic data (e.g., textbooks) and…
arXiv:2609.20816v2 Announce Type: replace-cross Abstract: Professional design requires any-color control: the ability to specify an object’s target color with any…
arXiv:2609.21562v2 Announce Type: replace-cross Abstract: Coding agents can modify and test code across large software projects. Game development is a…
arXiv:2609.23999v1 Announce Type: cross Abstract: How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood.…
arXiv:2609.24026v1 Announce Type: cross Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations…
arXiv:2609.19853v2 Announce Type: replace-cross Abstract: Between a screenplay and a film sits a planning problem that is spatial first: who…
arXiv:2609.21686v1 Announce Type: cross Abstract: Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval,…
arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical…
arXiv:2609.19569v2 Announce Type: replace-cross Abstract: Disease severity classification for genetic conditions is subjective and labor-intensive, creating bottlenecks in genomic screening,…