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Four LLMs were tested on structured clinical vignettes in otolaryngology, measuring both whether the model gave the right diagnosis and whether the citations it provided actually existed. Diagnostic performance varied across models, and citation hallucination was present — meaning models confidently cited non-existent sources. This matters because medical deployment of LLMs requires both accuracy and traceable evidence; fabricated citations undermine the auditing that makes clinical AI trustworthy.

██████████ 0.8 hallucination-grounding Peer-reviewed

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Using GPT-2 as a controlled testbed and logit-lens analysis to inspect layer-by-layer activations, the author identifies specific attention heads (L9H6 and L11H7) that systematically suppress factual tokens in favor of grammatically plausible ones — a phenomenon termed 'Grammatical Suppression of Facts.' The key claim is that this suppression is fact-specific: mathematical tokens experience near-zero suppression while factual tokens are suppressed ~70% of the time. Methodology is informal (single researcher, no peer review, no statistical testing), so these numbers should be treated as exploratory hypotheses rather than established results, but the mechanistic framing is concrete enough to be testable.

██████████ 0.8 hallucination-grounding Peer-reviewed

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An autonomous underwater vehicle was deployed at two coral reef sites using a combination of passive acoustic fish-call detection, YOLO-based visual fish counting, and 3D rugosity mapping to autonomously locate biological hotspots — and then navigate back to them via onboard homing. Nine homing experiments and one real-time barracuda tracking run demonstrate that multimodal sensing can close the perception-action loop in unstructured open-water environments. All data and analysis code are publicly archived with checksums, making this one of the more reproducible embodied-AI field deployments in the dataset.

██████████ 0.7 embodied-ai Peer-reviewed

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This companion dataset record to the Science Robotics study archives 5.3 GB of raw AUV sensor data including .wav hydrophone recordings, orthomosaic imagery, 3D mesh files, and odometry logs alongside all scripts needed to reproduce Figures 1–7. The significance for AI is methodological: it demonstrates how passive acoustics and visual detection can be fused via multimodal regression against environmental covariates (rugosity) to model biological activity — a template for sensor-fusion grounding in real-world autonomous systems.

██████████ 0.7 multimodal-understanding Peer-reviewed

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A four-agent LLM pipeline — Modeler, Implementer, Judge, Reporter — is proposed to autonomously generate mechanistic hypotheses, implement them in code, evaluate fit, and produce reports for pharmacological modeling tasks like tumor growth and drug resistance. The framework captured adaptive drug resistance through time-varying model components without manual intervention. This is a conference abstract only with no reproducibility details, so the claims cannot be verified, but the task decomposition pattern (generate → implement → evaluate → report) illustrates a concrete agentic architecture for scientific workflows.

██████████ 0.7 agent-tool-use Peer-reviewed

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A quadruped robot uses a vision-language model to estimate whether a nearby human is paying attention based on visual cues (early phase), then switches to Bayesian inference over the human's trajectory to assess whether they are actually adapting to the robot (later phase). These two signals are fused with phase-dependent weighting and fed into a chance-constrained motion planner. The idea that safety-relevant human state estimation requires different inference mechanisms at different interaction timescales is conceptually well-motivated, though the paper currently exists only as a .docx presentation with no experimental statistics.

██████████ 0.7 embodied-ai Peer-reviewed

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PVDF piezoelectric sensors combined with 1D convolutional neural networks achieve 94.6% accuracy at discriminating material hardness from tactile contact signals, with a median inference latency of 0.21 seconds on the Hannes prosthetic hand platform. A 64-channel distributed sensing array further achieves 94.7% spatial accuracy for localizing contact across fingers and palm. These are real hardware results with quantified performance, and the sub-second latency demonstrates that edge-deployable CNNs can close the tactile perception loop for prosthetics without cloud offloading.

██████████ 0.7 embodied-ai Peer-reviewed

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A multi-LLM judge panel was used to evaluate the complexity of AI-generated decision scenarios, achieving an intraclass correlation of ICC = .997 — indicating near-perfect agreement between LLM evaluators on a composite four-framework complexity instrument. This contributes to the question of whether LLMs can reliably serve as evaluators for AI-generated content, which matters for scalable quality control in synthetic data pipelines. The underlying paper content is not fully accessible, limiting assessment of sample size and statistical rigor.

██████████ 0.6 data-quality-curation 🔗 2 cited Peer-reviewed

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A scoping review synthesizes how AI systems can be designed to move from generating predictions to actually supporting or triggering decisions, with clinical decision support as the primary domain. The central problem it addresses is structural: most AI models optimize for predictive accuracy but are deployed in contexts where the relevant outcome is whether a decision improves — a gap that requires workflow integration, not just model performance. As a framework synthesis rather than an empirical study, it offers a taxonomy rather than new data.

██████████ 0.6 interpretability Peer-reviewed

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This theoretical paper decomposes the AGI alignment problem into outer alignment (correctly specifying what humanity wants as a final goal) and inner alignment (ensuring the system pursues that goal), then proposes a conceptual solution to outer alignment for superintelligent systems. The paper is written to be accessible to policymakers as well as technical audiences, which reflects a real gap in alignment discourse. The work is entirely philosophical with no formal proofs or empirical components, so the claimed 'solution' cannot be evaluated technically from the available abstract.

██████████ 0.5 alignment-safety Peer-reviewed

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