FineServe: A Fine-Grained Dataset and Characterization of Global LLM Serving Workloads
arXiv:2607.19349v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as always-on online services, making efficient LLM serving…
ChemHyperMag: Physics-informed magnetic hypergraph learning improves molecular ADMET prediction
arXiv:2607.18332v2 Announce Type: replace-cross Abstract: Accurate prediction of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) is important for drug discovery.…
Alignment of a Total Automation Economy
arXiv:2607.17015v2 Announce Type: replace-cross Abstract: We consider economic theory from the perspective of a total automation economy, one with no…
Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model
arXiv:2607.18958v1 Announce Type: cross Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their…
SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement
arXiv:2607.18960v1 Announce Type: cross Abstract: Procuring supervised fine-tuning (SFT) data forces a buyer to decide, before any downstream training, whether…
Enhancing Rubric-based RL via Self-Distillation
arXiv:2607.18082v2 Announce Type: replace-cross Abstract: Rubric-based RL has recently shown promise in improving LLMs on open-ended tasks. A widely recognized…
SysAdmin: Measuring Instrumental Power-Seeking in Frontier AI
arXiv:2607.18239v1 Announce Type: new Abstract: Power-seeking defined as behaviors where AI systems acquire resources, evade oversight, or resist termination beyond…
DCSCR: A Class-Specific Collaborative Representation based Network for Image Set Classification
arXiv:2508.12745v2 Announce Type: replace-cross Abstract: Image set classification (ISC), which can be viewed as a task of comparing similarities between…
Breaking the Factorization Barrier in Diffusion Language Models
arXiv:2603.00045v3 Announce Type: replace-cross Abstract: Diffusion language models theoretically allow for efficient parallel generation but are practically hindered by the…