Search papers, labs, and topics across Lattice.
29 papers published across 5 labs.
A multi-agent system using open-source LLMs outperforms leading models in detecting disinformation by mimicking human cognitive processes.
Generation trumps size in Text-to-SQL performance, with self-correction proving to be a game-changer across model families.
Context rot leads LLMs to falter under lengthy inputs, but targeted management and rejection strategies can restore their performance.
The openCOSMO-RS-Phi model achieves high accuracy in predicting thermodynamic properties while being fully open-source, democratizing access to advanced EoS tools.
Access to internal parameterizations can transform selfish optimization into cooperative outcomes in game-theoretic settings.
A multi-agent system using open-source LLMs outperforms leading models in detecting disinformation by mimicking human cognitive processes.
Generation trumps size in Text-to-SQL performance, with self-correction proving to be a game-changer across model families.
Context rot leads LLMs to falter under lengthy inputs, but targeted management and rejection strategies can restore their performance.
The openCOSMO-RS-Phi model achieves high accuracy in predicting thermodynamic properties while being fully open-source, democratizing access to advanced EoS tools.
Access to internal parameterizations can transform selfish optimization into cooperative outcomes in game-theoretic settings.
AlphaEdit's theoretical guarantees against catastrophic forgetting are not as unconditional as claimed, revealing critical sensitivities to model architecture and editing scale.
Emotion representation in LLMs varies dramatically across architectures, with some models encoding valence early and others later, revealing a complex landscape of emotional understanding in AI.
Selected features from sparse autoencoders can causally steer language models toward desired behaviors, like refusal, revealing new avenues for interpretability and control.
Distinguishing negative samples can boost LLM reasoning performance on ARC-like tasks by providing critical near-miss alternatives.
Reproducibility in quantum software datasets can drop dramatically, with 93.6% of failures tied to dependencies that demand code changes rather than simple version adjustments.
The ABC framework empowers researchers with the largest open-source teleoperation dataset and a complete toolkit to accelerate advancements in behavior cloning for robotic manipulation.
Annotation costs can be drastically reduced by shifting from manual labeling to correcting automated hypotheses in speaker diarization tasks.
CHIA revolutionizes hardware/software co-design by treating the design process as a first-class objective, enabling seamless integration of AI across diverse tools and workflows.
AI-assisted workflows can cut down experiment reproduction efforts by up to six times, but struggle with complex analysis tasks requiring human oversight.
Croc enables students to design and fabricate SoCs with open-source tools, achieving manufacturable results that rival those from closed-source environments.
AI coding agents are reshaping open-source ecosystems by diluting human participation while increasing the burden on code review processes.
Achieving a 12-cycle interrupt latency, CVA6-RT rivals simpler microcontrollers while delivering superior performance for mixed-criticality applications.
RaDaR can identify rare diseases 1.87 months earlier than traditional methods, revolutionizing diagnostic timelines for patients.
A staggering 79% of Claude Code adopters are overlooked by traditional pull-request analyses, revealing a critical blind spot in understanding AI's role in open-source development.
ComputeFHE cuts the computational costs of Fully Homomorphic Encryption by up to 3.9x, making privacy-preserving applications more feasible than ever.
Task success rates for agentic phone use soar from 36.67% to 45.33% through a novel combination of real and mock environments in training.
Federated learning in health research just got easier with FLKit, a structured onboarding toolkit that demystifies the process for diverse teams.
Only the right key can unlock the original image from diffusion models, turning a security risk into a robust feature against unauthorized reconstruction.
AOHP redefines how AI agents interact with operating systems, achieving a 21% boost in task completion and a dramatic cut in execution costs.
Bounded Context violations in DDD projects are shown to significantly hinder maintenance quality, revealing a critical challenge for practitioners.
The Composition event series has successfully bridged the gap between art and technology, sparking vibrant community engagement and collaboration.
Transitioning from restrictive to permissive licenses can either boost or hinder project activity, depending on the programming language used.
A staggering 39.4% of open source projects may be at risk of license noncompliance due to copy-based reuse, challenging the effectiveness of existing dependency tracking methods.
Controlled randomness in spiking neurons can significantly enhance edge hardware performance while minimizing area and noise sensitivity.
