The era of software engineering agents is underway. Benchmarks and real-world usage (e.g., tools like Cursor and Claude Code) illustrate that LLMs can be incredibly effective at writing code for real-world use-cases. Over…
Large language model (LLM)-based software engineering (SWE-) agents have recently demonstrated remarkable progress on realistic software engineering tasks such as code review, bug fixing, and repository-level reasoning. Most SWE-agents start from a fresh…
xGen-small is an enterprise-ready compact LM that combines domain-focused data-curation, scalable pre-training, length-extension, instruction fine-tuning, and reinforcement-learning to deliver Enterprise AI with long-context performance at predictable, low cost.
We present a novel architecture, BootPIG, that enables personalized image generation without any test-time fine-tuning.
TL;DR: With CodeChain, a pretrained large language model (LLM) can solve challenging coding problems by integrating modularity in generation samples and self-improve by employing a chain of self-revisions on representative sub-modules. CodeChain can…
TL;DR: Text-to-image diffusion models are very adept at generating novel images from a text prompt, but current adaptations of these methods to image editing suffer from a lack of consistency and faithfulness to…
