💻 Category

cs

2833 papers

💻 computer science

The Base-Rate Trap in Generative AI Text Detection: Why Detectors Cannot Serve as Standalone Evidence of Academic Misconduct, and Who Bears the Cost

This paper argues that generative AI text detectors are structurally unsuitable as standalone evidence of academic misconduct due to the base-rate fallacy, which causes unacceptably high false-positive rates and severe disparate impacts on non-native English writers, necessitating a shift from detection-based policing to assessment redesign.

TANZIM ISLAM KHAN2026-08-04
💻 computer science

Mapping the Convergence of Information Retrieval and Large Language Models

This paper presents a bibliometric analysis of 4,064 documents from 2015 to 2025, revealing that the Information Retrieval field has evolved from a diversifying landscape of distinct sub-areas into a converging structure centered on Large Language Models and neural ranking, driven by the bridging role of survey literature and the emergence of retrieval-augmented generation.

Prince Opoku Saaluon2026-08-04
💻 computer science

A Systematic Review and Taxonomy of GenAI Usage in Programming Education: A Self-Regulation Perspective

This systematic review of 58 studies up to October 2025 proposes a four-dimensional taxonomy to demonstrate that the impact of Generative AI on student self-regulation in programming education depends not on the technology itself, but on structured pedagogical mediation strategies that foster autonomy versus unguided contexts that encourage cognitive dependence.

Daniel Candido Oliveira, Pedro Santana, André L. Santos2026-08-04
💻 computer science

WiPAN: A Router-Mediated Personal Area Network Protocol Enabling Bluetooth-Equivalent Discovery and Communication over 802.11 Infrastructure

This paper presents WiPAN, a router-mediated protocol that leverages standard 802.11 infrastructure to deliver Bluetooth-equivalent device discovery and communication with significantly lower latency and higher scalability than traditional BLE, all without requiring dedicated Bluetooth hardware or Wi-Fi Aware chipset support.

Kunal Dhanda2026-08-04
💻 computer science

Resilient Supply Chain Optimisation under Geopolitical Disruptions: A Preference-Guided NSGA-II Approach for Multi-Criteria Decision Support

This paper proposes a preference-guided NSGA-II framework integrated with TOPSIS and VIKOR to optimize multi-objective supply chain decisions under geopolitical disruptions, demonstrating superior performance in balancing cost, service continuity, and resilience compared to five benchmark algorithms in humanitarian logistics scenarios.

Mahmoud M.Ibrahim, Ismail M. Ali, Shereen Zaki, Amal F. Abdel-Gawad, Mahmoud M. Ismail2026-08-04
💻 computer science

UGTC:Uncertainty-Gated Temporal Credit — A Modular Advantage Estimator for Actor-Critic RL

This paper introduces UGTC, a modular advantage estimator that dynamically blends fast and slow critics based on state-dependent epistemic uncertainty to significantly accelerate convergence and improve peak performance across multiple actor-critic algorithms, while providing rigorous analysis of its successes and specific failure modes.

Yağız Ekrem Dalar, Nedim Mutlu Sezer, Ömer Faruk Aksoy, Feyzi Arda Salihoğlu, Ahmet Rıfat Öztürk2026-08-04
💻 computer science

Exposing Contextual Amnesia in Vision–Language Segmentation: A Diagnostic Benchmark of Compositional, Relational, and Absence-Aware Referring Expressions

This paper exposes a critical "contextual amnesia" failure mode in state-of-the-art vision–language segmentation models, demonstrating through a new synthetic benchmark that these systems systematically collapse on relational, negation, and empty-target prompts despite strong attribute grounding, while showing that smaller, randomly initialized architectures and targeted adaptation techniques can significantly outperform existing billion-parameter cascades.

Yağız Ekrem Dalar, Nedim Mutlu Sezer, Ömer Faruk Aksoy, Feyzi Arda Salihoğlu, Ahmet Rıfat Öztürk2026-08-04
💻 computer science

Gradient-Free versus Gradient-Based Risk Constraints in Reinforcement Learning: A Reservoir Governance Case Study

This study demonstrates that in reservoir governance, gradient-free optimization (CEM) outperforms gradient-based methods (SAC/PPO) in minimizing tail risk because it directly evaluates non-differentiable CVaR, whereas gradient-based approaches suffer from geometrically decaying safety guarantees due to their reliance on differentiable cost surrogates.

Milad Tahavor, Soroush Amanna, Fatemeh Zabihi Jalali Zavareh, Milad Ghoroqi2026-08-04