Tootfinder

LeWiDi-2025 at NLPerspectives: The Third Edition of the Learning with Disagreements Shared Task
Elisa Leonardelli, Silvia Casola, Siyao Peng, Giulia Rizzi, Valerio Basile, Elisabetta Fersini, Diego Frassinelli, Hyewon Jang, Maja Pavlovic, Barbara Plank, Massimo Poesio
https://arxiv.org/abs/2510.08460…

LeWiDi-2025 at NLPerspectives: The Third Edition of the Learning with Disagreements Shared Task
Many researchers have reached the conclusion that AI models should be trained to be aware of the possibility of variation and disagreement in human judgments, and evaluated as per their ability to recognize such variation. The LEWIDI series of shared tasks on Learning With Disagreements was established to promote this approach to training and evaluating AI models, by making suitable datasets more accessible and by developing evaluation methods. The third edition of the task builds on this goal …

NoLBERT: A No Lookahead(back) Foundational Language Model for Empirical Research
Ali Kakhbod, Peiyao Li
https://arxiv.org/abs/2509.01110 https://arxiv.org/…

NoLBERT: A No Lookahead(back) Foundational Language Model for Empirical Research
We present NoLBERT, a lightweight, timestamped foundational language model for empirical research in social sciences, particularly in economics and finance. By pre-training exclusively on 1976-1995 text, NoLBERT avoids both lookback and lookahead biases that can undermine econometric inference. It exceeds domain-specific baselines on NLP benchmarks while maintaining temporal consistency. Applied to patent texts, NoLBERT enables the construction of firm-level innovation networks and shows that g…

Crosslisted article(s) found for q-fin.GN. https://arxiv.org/list/q-fin.GN/new
[1/1]:
- NoLBERT: A No Lookahead(back) Foundational Language Model for Empirical Research
Ali Kakhbod, Peiyao Li

HyperFlexis: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling
Zahra Yousefijamarani, Xinglu Wang, Qian Wang, Morgan Lindsay Heisler, Taha Shabani, Niloofar Gholipour, Parham Yassini, Hong Chang, Kan Chen, Qiantao Zhang, Xiaolong Bai, Jiannan Wang, Ying Xiong, Yong Zhang, Zhenan Fan
https://arxiv.org/abs/2508.15…

HyperFlexis: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling
Modern large language model (LLM) serving systems face challenges from highly variable requests with diverse lengths, priorities, and stage-specific service-level objectives (SLOs). Meeting these requires real-time scheduling, rapid and cost-effective scaling, and support for both collocated and disaggregated Prefill/Decode (P/D) architectures. We present \textbf{HyperFlexis}, a unified LLM serving system that integrates algorithmic and system-level innovations to jointly optimize scheduling …

Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
Nolbert Morales, Edward A. Turner
https://arxiv.org/abs/2508.12424 https://

Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
In this research, we present a generalized quasispecies model in which population growth is governed by an arbitrary nonlinear function incorporating time delays. We begin by demonstrating that, under the constant population constraint, the dynamics of the system with time delays remain confined to the invariant manifold for both forward and backward time evolution. Furthermore, we establish that in this modified quasispecies model, defined on a single-peak fitness landscape, in the presence of…