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Large Language Model (LLM)-based Test-Driven Development (TDD) has advanced automated code generation. However, exist...
Low-Rank Adaptation (LoRA) has become a widely adopted technique for efficient neural network fine-tuning, decomposin...
Automating theoretical research is constrained not only by the generation of candidate results, but also by their rel...
Commercial large language models are increasingly used as knowledge references, yet their stance on contested scienti...
A central design principle in modern machine learning and artificial intelligence is to align a model's inductive bia...
Adding procedural skills to an LLM agent is typically evaluated by average improvement in task success. However, this...
To effectively integrate AI into high-stakes, critical environments such as healthcare, autonomous driving, and aviat...
Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capabil...
LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing se...
Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existin...
Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-trai...
Recent conditional video generation models have shown promising potentials to transform 3D engine renderings, such as...