This Article examines the relationship between legal doctrine and remedial law through the lens of restitution, arguing that differences between American and English restitution jurisprudence stem less from divergent substantive rules than from competing assumptions about the roles of law, facts, rights, and judicial discretion. The Article contends that the development of legal doctrine is closely linked to whether a legal system conceptualizes a dispute as a question of law subject to appellate elaboration or as a fact-intensive matter committed to broad trial-court discretion. Using restitution and constructive trust doctrine as a comparative case study, the Article traces how English courts and scholars have developed a sophisticated body of restitutionary doctrine by treating questions of tracing, unjust enrichment, property rights, and equitable interests as legal issues requiring principled and systematic resolution. By contrast, American courts frequently characterize analogous disputes as matters of equity, remedial discretion, procedural administration, or jurisdiction, thereby reducing opportunities for the development of detailed substantive doctrine. The Article explores this divergence through analyses of tax restitution, tracing claims, constructive trusts, fraud recoveries, and ultra vires government contracts, demonstrating that English courts typically justify remedies by reference to underlying legal rights, whereas American courts are more likely to focus on equitable balancing and standards of review. The Article further argues that debates over constructive trusts illustrate broader differences in how the two legal traditions understand the relationship between rights and remedies. Ultimately, the Article concludes that the relative underdevelopment of restitution law in the United States reflects a broader shift in modern American jurisprudence away from private-law conceptual analysis and toward procedural, institutional, and discretionary frameworks for resolving disputes.[This abstract was written by Microsoft Copilot, a generative artificial intelligence.]
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9