
Language-model gains may come from diversity, not hidden experts
A preprint challenges a weight-space explanation for ensemble gains and tests a simpler output-level alternative.
- language models
- ensembles
- inference
CHANNEL ARCHIVE // [15] ARTICLES
Research into artificial intelligence and intelligent systems.
CHANNEL // 01 [15]
Research into artificial intelligence and intelligent systems.

A preprint challenges a weight-space explanation for ensemble gains and tests a simpler output-level alternative.

An arXiv preprint describes a pixel-space image generator that routes low-frequency information through global attention while handling other spectral detail locally.

An arXiv preprint studies how an end-to-end system might detect and match luggage across video streams, but its abstract does not report results.

A preprint describes WxCrop, an AI agent that combines weather and agricultural information to estimate crop losses, with initial tests covering three hazards in Florida.

An arXiv preprint finds that reading a visible scene from visual model representations does not guarantee that information persists, predicts future observations or supports useful action.

An arXiv preprint reports improved detection of watermarked language-model output, including under speculative decoding, while preserving output diversity.

An arXiv preprint reports that a single compact decoder performed competitively on automated measures of proactive, memory-grounded conversational hints, though human ratings favored a larger model.

In an arXiv preprint, researchers report that collaborating AI agents derived and tested predictions about quantum spins in diamond, revising an experiment after detecting signal drift.

In a controlled multi-agent study, a probe detected many imminent secret disclosures before output, but also flagged permitted disclosures and generated frequent episode-level alarms.

An arXiv preprint reports that neural-network clutter suppression improved position and velocity estimates in a modeled multistatic sensing framework, though the abstract provides no numerical results or real-world validation details.

An arXiv preprint describes a verifier that gathers evidence through interface and code checks, reporting better agreement with reference labels than compared baselines.

An arXiv preprint introduces agent-built robotics simulations and reports that leading models failed all test tasks, though several learning approaches improved performance.

A preprint reports similarities and differences in counselling communication patterns across role-plays with human peers and AI-simulated clients, but its abstract does not detail the results.

In an arXiv preprint, researchers describe a pipeline for making computational mathematics reusable by AI systems, with selected implications checked in Lean.

An arXiv preprint reports that ClinGeX matched expert classifications more often than comparators in a benchmark and was associated with higher concordance in a professional collaboration study.