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arXiv:2610.23917v1 Announce Type: new Abstract: An announced boundary reveals the partition before the first affected outcome, and a reset there serves one of two audits. The per-time audit reads conformal reliability, the expected distance…
arXiv:2610.23926v1 Announce Type: new Abstract: Fake accounts continue to undermine online platforms, yet it remains unclear whether multimodal learning offers meaningful improvements over strong metadata baselines or graph-based approaches. In this work, we study…
arXiv:2610.23923v1 Announce Type: new Abstract: Tabular data are prevalent across diverse domains such as healthcare and finance. Zero-shot tabular learning aims to make predictions without labeled data. However, existing LLM-based approaches rely on row-wise…
arXiv:2603.28733v3 Announce Type: replace Abstract: We propose using Vision-Language Models (VLMs) for macro placement in chip floorplanning, a complex optimization task that has recently shown promising advancements through machine learning methods. Because human designers…
arXiv:2610.23928v1 Announce Type: new Abstract: Native NVFP4 promises to accelerate reinforcement learning (RL) for large language models (LLMs), but achieving stable learning across separate training and sampling engines remains challenging. We show that matching…
arXiv:2507.10057v4 Announce Type: replace-cross Abstract: Scientific paper retrieval, particularly framed as document-to-document retrieval, aims to identify relevant papers in response to a long-form query paper, rather than a short query string. Previous approaches to…
arXiv:2609.15498v2 Announce Type: replace Abstract: Recurrent Transformers reusing their weights rather than stacking $L$ distinct layers are becoming widely adopted due to their parameter efficiency [1,2,3]. However, the exact representational and dynamical differences between…
arXiv:2610.25182v1 Announce Type: cross Abstract: Large-scale conversational recommendation datasets typically require manual dialogue construction or annotation. We propose SearCl, which automatically generates conversational recommendation dialogues grounded in user search and click behaviors. SearCl segments…
arXiv:2607.23258v3 Announce Type: replace-cross Abstract: Calcium imaging has enabled large-scale recordings of neural population activity across diverse animals, laboratories, and experimental paradigms. However, these datasets remain highly fragmented: Existing approaches are often designed for…
arXiv:2610.26324v1 Announce Type: cross Abstract: Trading discipline often fails people. Our study tested whether four AI trading agents followed their strategies and risk rules. Offering traders the evidence and an agent evaluation toolkit to…
arXiv:2610.25650v1 Announce Type: cross Abstract: Language models often change answers because of a cue, a hint such as "I believe the answer is B" that gives no valid evidence. Consistency training (CT) trains a…
arXiv:2607.22954v2 Announce Type: replace Abstract: Objective:To characterize the kinds of internal documentation inconsistencies a general-domain large language model (LLM) can surface from real-world discharge summaries, and to identify recurring failure modes that limit reliability…