Spice
PulseAugur coverage of Spice — every cluster mentioning Spice across labs, papers, and developer communities, ranked by signal.
6 day(s) with sentiment data
-
Amazon Quick adds live data querying to AI-built apps
Amazon Quick has introduced a new feature called Live Data in Apps, which allows AI-built applications to query governed Amazon Quick Sight datasets in real time. Previously, apps could only display data that was static…
-
New research advances causal inference methods for AI models · 6 sources tracked
Researchers are developing new methods to improve causal inference in machine learning models, particularly when dealing with unmeasured confounding factors. One approach, Hidden-Pathway Contribution (HPC), aims to dist…
-
New AI framework creates interpretable transistor models for advanced chips
Researchers have developed PRISM-UDE, a novel framework for creating accurate and physically interpretable transistor models. This approach embeds a neural network within a physics-based model to learn complex transport…
-
New SPICE framework simplifies polysemanticity analysis in vision models
Researchers have developed SPICE, a novel framework designed to simplify the analysis of polysemanticity in deep vision architectures. This new method offers a generalizable approach that is not tied to specific model a…
-
vd_agent project aims to revive early 2000s SPICE VM monitor
The vd_agent project aims to revive SPICE, a virtual machine monitor that was popular in the early 2000s. The project's creator, Lloyd Bloch, is committed to keeping SPICE alive and functional. This initiative seeks to …
-
New AI tutor transforms static circuit problems into dynamic learning experiences
Researchers have developed CircuTutor, an intelligent tutoring system designed to enhance the learning of direct current circuit concepts. This system transforms static circuit problems from textbooks into dynamic, inte…
-
AI's circuit board design capabilities tested by new EEBench framework
A new evaluation framework called EEBench is being developed to assess the capabilities of AI in designing electronic circuits, particularly printed circuit boards (PCBs). While AI models like OpenAI's GPT-6 Astra demon…
-
New PCBnet Dataset and Pipeline Boost AI in Circuit Board Design
Researchers have introduced PCBnet, a new dataset designed to advance AI-driven automation in printed circuit board (PCB) design. This dataset includes over 300 real-world PCB designs, featuring more than 50,000 compone…
-
SPICE framework enhances reproducibility in deep learning for Predictive Process Mining
Researchers have introduced SPICE, a new Python framework built with PyTorch, designed to enhance reproducibility in Predictive Process Mining (PPM). SPICE standardizes the implementation of three popular deep learning-…
-
LLM-SPICEMixer enhances analog circuit design with LLM-guided genetic algorithms
Researchers have developed LLM-SPICEMixer, a novel framework that enhances genetic algorithms for analog circuit design. This hybrid approach integrates an LLM-based operator, IGEL, to generate new circuit netlist propo…
-
LLMs accelerate analog circuit design with new frameworks for layout and topology
Two new research papers explore the application of large language models (LLMs) in analog circuit design, aiming to automate and improve the efficiency of complex layout refinement and topology generation. The first pap…
-
New benchmark reveals LLM limitations in circuit design netlist manipulation
Researchers have introduced NetlistBench, a new benchmark designed to evaluate the reliability of Large Language Models (LLMs) in understanding and manipulating SPICE netlists, which are crucial for circuit design. The …
-
New CapProbe benchmark evaluates detailed image captions from VLMs
Researchers have introduced CapProbe, a new benchmark designed to rigorously evaluate the detailed captions generated by vision-language models (VLMs). Unlike existing metrics that struggle with factual accuracy and pro…
-
Adjudicated Captioning framework boosts zero-shot image captioning performance
Researchers have developed a novel multi-agent framework called Adjudicated Captioning to improve zero-shot image captioning. This inference-time system enhances an existing captioner by adding a stronger retrieval enco…
-
LLM Agents Tackle Analog Circuit Design with ATLAS Framework
Researchers have developed a new framework called ATLAS that leverages Large Language Models (LLMs) for analog Electronic Design Automation (EDA). This multi-step agentic framework is designed to generate functional Suc…
-
Amazon Quick Sight integrates business context into datasets and unifies multiple datasets with new Topic features
Amazon Quick Sight is enhancing its data management capabilities with two new features: Dataset Enrichment and multi-dataset Topics. Dataset Enrichment allows business context, such as column descriptions and synonyms, …
-
Weave tool achieves 100% verified schematic conversion accuracy
Researchers have developed Weave, a new deterministic tool for converting SPICE netlists into LTspice schematics. Unlike probabilistic methods that offer no connectivity guarantees, Weave provides a binary correctness c…
-
New memristive synapse design promises highly efficient on-chip neural networks
Researchers have developed a physics-based design for an on-chip neural network utilizing multi-level memristive synapses capable of supporting a wide range of conductance states. This design, rooted in ionic transport …
-
LLM framework generates verifiable PCB schematics without unit tests
Researchers have developed PCBSchemaGen, a novel framework designed to enable large language models (LLMs) to generate verifiable code for printed circuit board (PCB) schematic designs. Unlike typical code synthesis ben…
-
SPICE framework enhances multimodal learning with dynamic curriculum evolution
Researchers have introduced SPICE, a new framework for multimodal learning that dynamically adapts curriculum based on Partial Information Decomposition (PID) theory. This approach breaks down multimodal interactions in…