…View arXiv page View PDF Project page GitHub 1 Add to collection Community We introduce CurveBench, a benchmark for testing whether vision-language models can recover hierarchical region-containment trees from images…
…It could also discuss how developers can contribute to or build upon these models, aligning with the library’s modularity and community-driven approach. Recent Developments (as of January 2025): Given the…
…The typical industry recipe involves a highly resource-intensive pipeline spanning pre-training, continual pre-training (CPT), supervised fine-tuning (SFT), and reinforcement learning (RL). In this report, we show that when…
…We hope that AcademiClaw and its open-sourced data and code can serve as a useful resource for the OpenClaw community, driving progress toward agents that are more capable and versatile across…
…whether Large Language Models can judge the methodological viability of a research idea before expending time and computational resources. We introduce SoundnessBench, a curated benchmark of 1,099 machine-learning research proposals…
…A Resource-Aware Training Runtime for Large Language Models on Bandwidth-Constrained Heterogeneous Supercomputing Platforms (2026) A Tabular Schedule Abstraction for Communication-Aware Evaluation of Pipeline-Parallel LLM Training (2026) Schedule-Level…
…View arXiv page View PDF Add to collection Community Visual ParaThinker++ This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers…
…View arXiv page View PDF GitHub 15 Add to collection Community Agent libOS proposes a library-OS-inspired runtime substrate for long-running LLM agents. Instead of treating model-visible tools as…
…View arXiv page View PDF Add to collection Community EverAnimate code, 480p LoRA checkpoints, minimal demo data, and training/inference scripts are now released: https://huggingface.co/epfl-vita/everanimate Resources: Code…
…View arXiv page View PDF GitHub 43 Add to collection Community Traditional indexing for large language model personalization and search can be rigid and resource-intensive. In this paper, we explore a…