99 papers
This collection explores the dynamic frontier of research spanning from carbon nanotubes to organic semiconductors, where chemists and materials scientists are redefining what is possible at the atomic scale. These studies investigate how molecular structures interact to create new technologies, often bridging the gap between theoretical chemistry and real-world applications like flexible electronics or advanced energy storage.
Every new preprint in this category arrives directly from arXiv, and Gist.Science immediately processes each submission to make the findings accessible to everyone. We provide both clear, plain-language overviews for general readers and detailed technical summaries for specialists, ensuring that complex discoveries in this rapidly evolving field are easy to understand and verify. Below are the latest papers exploring these groundbreaking materials and their transformative potential.
RTP-LLM is a high-performance, open-source inference engine deployed at Alibaba Group that achieves superior throughput and latency reductions compared to vLLM and SGLang through integrated optimizations like Prefill-Decode Disaggregation, hierarchical KV cache management, and modular speculative decoding.
Sandlock is a lightweight, unprivileged Linux sandbox that isolates AI agents by compiling static security policies into kernel-enforced rules while delegating runtime decisions to a narrow supervisor, thereby achieving strong confinement without the overhead of containers, microVMs, or root privileges.
This paper introduces Virtual Library Contexts (VLCs), a process-level mechanism that encapsulates software libraries and their resource allocations to enable safe, high-performance parallel execution of non-composable or thread-unsafe libraries without requiring modifications to the library code or operating system.
This paper presents a formal, per-access analytical proof establishing that the maximum credible interference stall for a task in a direct-mapped multicore processor with specific architectural invariants is strictly bounded by (N-1)Lmem, thereby providing a traceable method for certifying airborne software under DO-178C/CAST-32A standards.
This paper introduces DeltaBox, a novel sandbox system leveraging the OS-level abstractions DeltaFS and DeltaCR to achieve millisecond-level checkpoint and rollback by duplicating only state changes rather than full system states, thereby enabling high-frequency exploration for LLM-powered AI agents.
This paper introduces THEMIS, an enhanced fair scheduling algorithm for multi-tenant FPGAs that improves upon existing methods by incorporating spatiotemporal fairness, energy efficiency, and hardware heterogeneity constraints, resulting in significant gains in fairness and energy-fairness trade-offs.
This paper presents Clove, a system that extends managed language runtimes with profile-guided hotness tracking and object relocation policies to enable efficient object-level CXL memory management, significantly outperforming traditional page-based systems by reducing application slowdown by 22–84%.
ParaCell is a paravirtualized secure container runtime that resolves the isolation-performance trade-off by leveraging MPK-based XGates for lightweight intra-container domain switching and a Pager mechanism for intent-driven, proactive memory management, thereby significantly reducing latency and memory overhead in both traditional and agentic workloads.
Skim is a speculative execution framework that significantly reduces the cost and latency of web agents by leveraging predictable website structures to bypass heavyweight inference components for most queries, while using a lightweight verifier to ensure accuracy and seamlessly cascade rare failures to full agents.
This paper introduces OSWorld-Human, a manually annotated benchmark revealing that current computer-use agents suffer from prohibitive latency and inefficiency, primarily due to excessive model calls for planning and reflection, resulting in them taking 2.7 to 4.3 times more steps than humans to complete tasks.