Search papers, labs, and topics across Lattice.
24 papers published across 1 lab.
Accurately assessing contributor competences could be the key to revitalizing disengaged OSS projects and ensuring their long-term viability.
Optimizing developer assignments based on expertise can boost task completion efficiency by over 70% in open-source projects.
Some large language models exhibit surprising human-like sensitivity to discourse factors in anaphor resolution, but falter on semantic interference.
An open-source power measurement platform enables automated, reproducible testing of embedded systems, transforming how researchers evaluate energy efficiency.
Algorithm rankings in anomaly detection are highly unstable, with nearly every method capable of claiming top performance under different benchmark conditions.
Accurately assessing contributor competences could be the key to revitalizing disengaged OSS projects and ensuring their long-term viability.
Optimizing developer assignments based on expertise can boost task completion efficiency by over 70% in open-source projects.
Some large language models exhibit surprising human-like sensitivity to discourse factors in anaphor resolution, but falter on semantic interference.
An open-source power measurement platform enables automated, reproducible testing of embedded systems, transforming how researchers evaluate energy efficiency.
Algorithm rankings in anomaly detection are highly unstable, with nearly every method capable of claiming top performance under different benchmark conditions.
Gradient Immunity can significantly hinder malicious fine-tuning efforts, keeping attack success rates at pre-release levels while enhancing safety without user intervention.
HoRFFI achieves remarkable gains in novel-class accuracy and AUC, proving that high-openness RFFI can be effectively addressed with minimal labeled data.
Agent Plans in open-source repositories reveal critical insights into how AI coding tools can be effectively guided through structured task-oriented artifacts.
CheMLFlow slashes the orchestration overhead in scientific machine learning, enabling researchers to focus on their core contributions without getting bogged down in workflow complexities.
K-EXAONE 2.0 achieves over three times the capacity of its predecessor while enhancing multilingual capabilities and long-context reasoning.
AI governance policies can significantly enhance developer experience on GitHub, with transparency-focused strategies yielding better community and quality outcomes.
Coding agents boost task completion rates by over 30%, but at the cost of diminishing public knowledge resources for future developers.
MalTotal uncovers 564 previously unknown malicious repositories while slashing analysis costs from $86.25 to just $5.19.
PECR outperforms traditional vulnerability prioritization methods, achieving a Kendall τ value of 0.924, highlighting the critical role of contextual factors in effective risk management.
POVGEN generates Proofs-of-Vulnerability for 78.98% of cases, revealing flaws in existing patches and uncovering new vulnerabilities, all while minimizing costs.
Developers face significant integration barriers in SSI frameworks, particularly with schema customization, revealing a critical gap in current tooling.
The rise of AI in software development is rendering traditional software measurement assumptions obsolete, necessitating a radical rethink of how we validate our findings.
Z-PEFT reveals that traditional backdoor detection methods fail in zero-shot scenarios, highlighting the need for robust, adaptable solutions in model safety.
Open-DiffLoco achieves robust quadruped locomotion with minimal training complexity, outperforming traditional reinforcement learning methods.
The D-profile Ginga DTV receiver specification could revolutionize how Brazilian viewers interact with digital content, merging broadcast and broadband services seamlessly.
Despite high user satisfaction with LLM interactions, a staggering 23.1% of goal tasks failed, challenging assumptions about conversational success.
Open-source software development can boost profitability by 4-5%, but only when firms effectively integrate external contributions into their workflows.
MADE transforms the labor-intensive process of model deployment into a streamlined, automated workflow, achieving a notable 68.85% success rate in making models ready-to-call APIs.
Achieving 1,500 tokens per second, DiffusionGemma redefines the speed-capability trade-off in language models, outpacing conventional autoregressive approaches.
