Check computer science papers: citations, claims and retractions

Energy-Based Transformers are Scalable Learners and Thinkers

Gladstone, A., Nanduru, G., Islam, M. M., Han, P., Ha, H., Chadha, A., Du, Y., Ji, H., Li, J., & Iqbal, T. (2025) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1

Many-to-Many Prediction for Effective Modeling of Frequent Label Transitions in Time Series

Katrompas, A., & Metsis, V. (2024) · Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments

Time Series Analysis and ForecastingStock Market Forecasting Methods

Cited by 1

How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models

Asawa, P., Zhu, A., O'Neill, A., Zaharia, M., Dimakis, A. G., & Gonzalez, J. E. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1

Claim Plane: Enforceable Change Intents and Dynamic Scope for Parallel Coding Agents

Nikolaev, M. (2026) · arXiv

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 1

Can LLM Agents Really Debate? A Controlled Study of Multi-Agent Debate in Logical Reasoning

Wu, H., Li, Z., & Li, L. (2025) · arXiv

Multi-Agent Systems and NegotiationLogic, Reasoning, and Knowledge

Cited by 1

Build Agent Advocates, Not Platform Agents

Kapoor, S., Kolt, N., & Lazar, S. (2025) · arXiv

Ethics and Social Impacts of AIDigital Platforms and Economics

Cited by 1

SWE-Bench-CL: Continual Learning for Coding Agents

Joshi, T., Chowdhury, S., & Uysal, F. (2025) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 1

From Commands to Prompts: LLM-based Semantic File System for AIOS

Shi, Z., Mei, K., Jin, M., Su, Y., Zuo, C., Hua, W., Xu, W., Ren, Y., Liu, Z., Du, M., et al. (2024) · arXiv

Information Retrieval and Search BehaviorAdvanced Data Storage Technologies

Cited by 1

A systematic review and meta-analysis on the neural correlates of bodily self-consciousness

Brunello, N., Diana, L., Sritharan, J., Glisic, M., Nef, T., Verma, R. K., & Zito, G. A. (2025) · Neuroscience & Biobehavioral Reviews

Virtual Reality Applications and ImpactsFree Will and Agency

Cited by 1

Anomaly Subgraph Detection through High-Order Sampling Contrastive Learning

Sun, Y., Wang, W., Wu, N., & Bao, C. (2024) · Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence

Advanced Graph Neural NetworksAnomaly Detection Techniques and Applications

Cited by 1

Reliability without Validity: A Systematic, Large-Scale Evaluation of LLM-as-a-Judge Models Across Agreement, Consistency, and Bias

Norman, J. D., Rivera, M. U., & Hughes, D. A. (2026) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1

Coordination Overhead and Governance Readiness in Distributed LLM Multi-Agent Systems: An Empirical Architecture Evaluation

Mahajan, A. (2026) · SSRN Electronic Journal

Multi-Agent Systems and NegotiationAI-based Problem Solving and Planning

Cited by 1

AdaCoder: Adaptive Prompt Compression for Programmatic Visual Question Answering

Ukai, M., Kurita, S., Hashimoto, A., Ushiku, Y., & Inoue, N. (2024) · Proceedings of the 32nd ACM International Conference on Multimedia

Multimodal Machine Learning ApplicationsSoftware Engineering Research

Cited by 1

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

Grazzi, R., Siems, J., Zela, A., Franke, J. K. H., Hutter, F., & Pontil, M. (2024) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 1

An Introduction to PHP

(2006) · Beginning PHP and MySQL 5

Mobile and Web ApplicationsWeb Applications and Data Management

Cited by 1

Can Emulating Semantic Translation Help LLMs with Code Translation? A Study Based on Pseudocode

Chen, S., Xu, C., Chen, J., Cao, J., Wu, J., & Cheung, S.-C. (2026) · ACM Transactions on Software Engineering and Methodology

Software Engineering ResearchNatural Language Processing Techniques

Cited by 1

Benchmark on Peer Review Toxic Detection: A Challenging Task with a New Dataset

Luo, M., Peterson, B., Gan, R., Ramalingame, H., Gangrade, N., Dimarogona, A., Banerjee, I., & Howard, P. (2025) · arXiv

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 1

Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers

Pacchiardi, L., Tesic, M., Cheke, L. G., & Hernández-Orallo, J. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Derailer-Rerailer: Adaptive Verification for Efficient and Reliable Language Model Reasoning

Wan, G., Wu, Y., Wang, H., Zhao, S., Chen, J., & Li, S. (2025) · Findings of the Association for Computational Linguistics: ACL 2025

Formal Methods in VerificationNatural Language Processing Techniques

Cited by 1

Data structures and algorithms misconceptions in concept inventories: a systematic literature review

Tilanterä, A., & Korhonen, A. (2026) · Computer Science Education

Teaching and Learning ProgrammingScience Education and Pedagogy

Cited by 1

AI and HR: Exploring the Ethical Implications of Algorithmic Hiring

Mahapatra, T. (2025) · Training and Development Journal

Ethics and Social Impacts of AIAI and HR Technologies

Cited by 1

ClawSafety: "Safe" LLMs, Unsafe Agents

Wei, B., Zhang, Y., Pan, J., Mei, K., Wang, X., Hamm, J., Zhu, Z., & Ge, Y. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1

Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers

Du, P. (2026) · arXiv

AI-based Problem Solving and PlanningTopic Modeling

Cited by 1

BAQE: Backend-Adaptive DNN Deployment via Synchronous Bayesian Quantization and Hardware Configuration Exploration

Zhao, W., Yin, S., Bai, C., Wang, Z., & Yu, B. (2025) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 1