Search papers, labs, and topics across Lattice.
18 papers published across 0 labs.
DataFlex-RL, an evaluation platform for comparing choices under a common GRPO recipe, is introduced, finding that changing the data policy measurably changes the training process but does not produce a reproducible improvement over uniform training.
Seizure detectors may perform well on clean data but can falter dramatically under real-world conditions, revealing a critical gap in pre-deployment assessments.
The first open Armenian LLM, arm-gemma-e4b, not only outperforms all predecessors but also highlights the critical balance between fluency and knowledge retention in low-resource language models.
WebXR could be the key to a more accessible and sustainable Metaverse, challenging the dominance of commercial game engines.
High-fidelity image synthesis does not require paired text from day one: pre-training visual priors on uncaptioned images before multimodal alignment beats conventional joint training pipelines to establish a new open-source DiT benchmark.
DataFlex-RL, an evaluation platform for comparing choices under a common GRPO recipe, is introduced, finding that changing the data policy measurably changes the training process but does not produce a reproducible improvement over uniform training.
Seizure detectors may perform well on clean data but can falter dramatically under real-world conditions, revealing a critical gap in pre-deployment assessments.
The first open Armenian LLM, arm-gemma-e4b, not only outperforms all predecessors but also highlights the critical balance between fluency and knowledge retention in low-resource language models.
WebXR could be the key to a more accessible and sustainable Metaverse, challenging the dominance of commercial game engines.
High-fidelity image synthesis does not require paired text from day one: pre-training visual priors on uncaptioned images before multimodal alignment beats conventional joint training pipelines to establish a new open-source DiT benchmark.
Governance metrics in agricultural open-source software reveal surprising independence from actual security risks, challenging assumptions about the sector's vulnerability.
Uncovering recurring implementation patterns in LLM codebases could revolutionize how developers approach building and optimizing AI applications.
Boundary-mutation testing uncovers critical vulnerabilities in secret scanners, revealing that some rules can fail completely under realistic context variations.
MutMem V2 achieves portable integrity and reproducibility in persistent agent memory, setting a new standard for cryptographic authorization in AI systems.
Weak governance in standards-setting organizations is pushing geospatial coordination towards proprietary platforms, threatening the very essence of open standards as public goods.
Traditional knowledge graph matchers fall short, with LLMs outperforming them by a significant margin in threat report evaluations.
A leading-order effective field links empirical dynamics to neural computation, revealing how human-AI interactions exhibit reproducible and interpretable patterns.
Disagreement among evaluators can be systematically bounded, revealing critical insights into the reliability of natural language task assessments.
Hand-written behavioral clock gating fails at gate level, while tool-inserted ICG cells achieve robust power savings across all simulation corners.
Achieving competitive performance in full-key side-channel attacks on uncropped datasets with a simple transformer model could revolutionize the field by making advanced techniques more accessible.
Feedback effectiveness in LLM code repair is not universally applicable across programming languages, challenging previous assumptions about its reliability.
Experimental records in autonomous driving can now be seamlessly integrated with real-time operational conditions, enhancing interpretability and reuse across teams.
Achieving 95.7% precision in parameter extraction, this open-weights model challenges the reliance on commercial systems for reproducible agentic workflows in materials science.
