…constructive criticism from the community. This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers were recommended by the Semantic Scholar…
…View arXiv page View PDF Project page Add to collection Community i think this is a fascinating work, very timely in this field. thank you for your contribution to the community! the…
…For direct interaction, acting on uncertainty means communicating it honestly; for agentic systems, it becomes the control layer governing when to search and what to trust. Metacognition is thus essential for LLMs…
…56 Add to collection Community This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers were recommended by the Semantic Scholar…
…Diversity in Evolutionary Inference , a distributed Quality-Diversity (QD) search framework that assigns heterogeneous large language models (LLMs) as mutation operators across peer nodes communicating with non-blocking collective operations . Unlike homogeneous…
…Pipeline parallelism combined with CPU offloading mitigates these hardware bottlenecks by reducing communication overhead. However, existing PP schedules suffer from an inherent limitation termed the weight binding issue . Binding uneven model stages…
…We release our German language models (called Boldt), as well as our cleaned evaluation benchmarks to the research community. Our experiments indicate that they achieve state-of-the-art results despite training…
…We release SWE-WebDev Bench as a community benchmark to enable such replication and help platform builders identify and address these gaps. Code and benchmark resources are available at: https://github.com…
…Community Introduce on-policy distillation to flow matching models. This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers were recommended…
…View arXiv page View PDF Project page GitHub 70 Add to collection Community Real tasks can grow almost unbounded, yet a model's context is finite. We teach agentic LLMs delegation intelligence…