Check computer science papers: citations, claims and retractions

From Accountable Records to Observable Decision Processes: Provenance Requirements for Human-AI Decision Systems

Novik, D. (2026) · SSRN Electronic Journal

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 0

MemTrace: Probing What Final Accuracy Misses in Long-Term Memory

Long, X., Chen, Z., Zeng, S., Wang, S., Guo, K., & Tang, J. (2026) · arXiv

AI-based Problem Solving and PlanningInformation Retrieval and Search Behavior

Cited by 0

ReST-KV: Robust KV Cache Eviction with Layer-wise Output Reconstruction and Spatial-Temporal Smoothing

An, Y., Lu, C., Zhu, K., Yu, T., Zhao, C., Wu, H., Tang, M., & Wang, J. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

One-shot Entropy Minimization

Gao, Z., Chen, L., Luo, H., Zhou, J., & Dai, B. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 0

RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback

Miao, C., Zou, H. P., Li, Y., Chen, Y., Wang, Y., Wang, F., Li, Y., Yang, W., He, B., Zhang, X., et al. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0

SparseX: Efficient Segment-Level KV Cache Sharing for Interleaved LLM Serving

Zhang, Q., Chen, K., Liao, N., Lin, Z., Tang, B., Xiong, F., Li, Z., & Wang, X. (2026) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 0

JEPA-Anything: Learning Predictive Models across Different Worlds

Cui, T., Wang, Z., Xu, X., Liu, W., Yu, Z., Zhang, Y., Gao, Q., Yang, M., Ouyang, W., Heng, P. A., et al. (2026) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 0

PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving

Woo, S., Kim, H., Shim, S., Jo, M., Jeong, H., Lee, J., Kim, J., Lee, S., Ryu, J., Park, B., et al. (2026) · arXiv

Natural Language Processing TechniquesParallel Computing and Optimization Techniques

Cited by 0

Measuring Collapse and Correction in Homogeneous-Panel LLM Debate

Li, X., Liu, M., & Yuen, C. (2026) · arXiv

Topic ModelingMulti-Agent Systems and Negotiation

Cited by 0

Computer Environments Elicit General Agentic Intelligence in LLMs

Cheng, D., Huang, S., Gu, Y., Song, H., Chen, G., Dong, L., Zhao, W. X., Wen, J.-R., & Wei, F. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling

Huang, H., Zhu, D., Wu, B., Zeng, Y., Wang, Y., Min, Q., & Zhou, X. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

ThunderAgent: A Simple, Fast and Program-Aware Agentic Inference System

Kang, H., Li, Z., Xu, W., Yang, X., Chen, Y., Wang, J., Chen, B., Krishna, T., Xu, C., & Arora, S. (2026) · arXiv

Parallel Computing and Optimization TechniquesCloud Computing and Resource Management

Cited by 0

Adversarial Unsupervised Representation Learning for Activity Time-Series

Aggarwal, K., Joty, S., Fernandez-Luque, L., & Srivastava, J. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 0

Self-supervised learning based on local attention encoding module for human activity recognition with wearable data

Chu, J., Zhang, Y., Wang, X., & Chen, W. (2025) · Fourth International Conference on Algorithms, Microchips, and Network Applications (AMNA 2025)

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 0

Length Generalization Bounds for Transformers

Yang, A., Bergsträßer, P., Zetzsche, G., Chiang, D., & Lin, A. W. (2026) · Zenodo

semigroups and automata theoryComputability, Logic, AI Algorithms

Cited by 0

Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents

Jaiswal, R., Jain, D., Popat, H. P., Anand, A., Dharmadhikari, A., Marathe, A., & Shah, R. R. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 0

Towards Agentic AI Networking in 6G: A Generative Foundation Model-as-Agent Approach

Xiao, Y., Shi, G., & Zhang, P. (2025) · arXiv

Software-Defined Networks and 5GAdvanced Data and IoT Technologies

Cited by 0

AGDecode: Semantic Attribute Grammar Derivatives for Safety-Constrained Decoding of Large Language Models

Maghera, R., Arya, A. T., Babikian, A. A., Chechik, M., & Dehnavi, M. M. (2026) · arXiv

Logic, programming, and type systemsSoftware Testing and Debugging Techniques

Cited by 0

Role-Augmented Intent-Driven Generative Search Engine Optimization

Chen, X., Bao, J., Wu, H., Chen, Z., Pan, L., & Liao, Y. (2025) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 0

HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation

Ouyang, J., Pan, T., Cheng, M., Yan, R., Luo, Y., Lin, J., & Liu, Q. (2025) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1

Zhou, K., Liu, C., Zhao, X., Jangam, S., Srinivasa, J., Liu, G., Song, D., & Wang, X. E. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0

C-SEO Bench: Does Conversational SEO Work?

Puerto, H., Gubri, M., Green, T., Oh, S. J., & Yun, S. (2025) · arXiv

Information Retrieval and Search BehaviorWeb visibility and informetrics

Cited by 0

Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models

Sui, Y., He, Y., Cao, T., Han, S., Chen, Y., & Hooi, B. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Never the Number: Structural Abstention for AI Systems Whose Answers Are Consumed as Fact

Zhelun, & Wu (2026) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 0