Results for "code generation".

FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean

Formalising informal mathematical reasoning into formally verifiable code is a significant challenge for large language models. In scientific fields such as physics, domain-specific machinery (\textit…

Balatro's mind-bending code uses mouse jitter for random number generation, along with a bunch of clever maths I'm too dense to fully appreciate

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise, it remains unclear …

LEGO: An LLM Skill-Based Front-End Design Generation Platform

Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design and debugging strategies. We present LEGO, a un…

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scalable, while automate…

Xiaomi releases MiMo-v2.5 Family weights with strong coding and agent benchmarks

Peking University gives its computer science students a compiler project every semester. Build a complete SysY compiler in Rust including lexer, parser, abstract syntax tree, IR code generation, assem…

Thinking Like a Clinician: A Cognitive AI Agent for Clinical Diagnosis via Panoramic Profiling and Adversarial Debate

The application of large language models (LLMs) in clinical decision support faces significant challenges of "tunnel vision" and diagnostic hallucinations present in their processing unstructured elec…

Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning

Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit step-by-step reasoning before generating final ans…

Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket

With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical environments. A review of the relevant open-source to…

Explanation Quality Assessment as Ranking with Listwise Rewards

We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single "best" explanation token-by-token, we train reward…

Microsoft TRELLIS.2: An Open-Source, 4B-Parameter, Image-to-3D Model [pdf]

Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, which struggle to capture assets with com…

Skymizer Taiwan Inc. Unveils Breakthrough Architecture Enabling Ultra-Large LLM Inference on a Single Card

Source Article excerpt: With a single PCIe card — powered by six HTX301 chips and 384 GB of memory — enterprises can now run 700B-parameter model inference locally at just ~240W per card. The memory-b…