Check computer science papers: citations, claims and retractions

Design and Implementation of a Lightweight Neural Controller for LLM Agent Systems

Langay, B. B. (2026) · International Journal of Latest Technology in Engineering Management & Applied Science

Topic ModelingNatural Language Processing Techniques

Cited by 0

A Topology-Aware, Memory-Centric Architecture that Separates Root-Cause Derivation from Root-Cause Explanation

Seedat, M. (2026) · arXiv

Software System Performance and ReliabilityDistributed systems and fault tolerance

Cited by 0

RedKnot: Efficient Long-Context LLM Serving with Head-Aware KV Reuse and SegPagedAttention

Liu, Y., Luo, Z., Jin, H., Wang, Z., He, R., Wang, B., Chen, G., Liu, Y., Xie, T., & Hu, J. (2026) · arXiv

Parallel Computing and Optimization TechniquesNatural Language Processing Techniques

Cited by 0

Improving Environment Novelty Quantification for Effective Unsupervised Environment Design

Teoh, J., Li, W., & Varakantham, P. (2024) · Advances in Neural Information Processing Systems 37

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 0

SEVerA: Verified Synthesis of Self-Evolving Agents

Banerjee, D., Xu, C., Ie, E., Zhang, M., Peng, D., Lin, C.-C., Suresh, T., & Singh, G. (2026) · arXiv

Logic, programming, and type systemsFormal Methods in Verification

Cited by 0

AMemGym: Interactive Memory Benchmarking for Assistants in Long-Horizon Conversations

Jiayang, C., Ru, D., Qiu, L., Li, Y., Cao, X., Song, Y., & Cai, X. (2026) · arXiv

Speech and dialogue systemsInformation Retrieval and Search Behavior

Cited by 0

Cross-Model KV Cache Transfer in LLM Families: A Closed-Form Linear Mapping for Prefill Reuse

Heo, T., Shafipour, R., Zhao, R., Golub, M., Kamani, M. M., Borkar, R., Chandran, M. T., Zardoshti, P., & Rouhani, B. D. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Controlled LLM Training on Spectral Sphere

Xie, T., Luo, H., Tang, H., Hu, Y., Liu, J. K., Ren, Q., Wang, Y., Zhao, W. X., Yan, R., Su, B., et al. (2026) · arXiv

Stochastic Gradient Optimization TechniquesTopic Modeling

Cited by 0

DialSim: A Dialogue Simulator for Evaluating Long-Term Multi-Party Dialogue Understanding of Conversational Agents

Kim, J., Chay, W., Hwang, H., Kyung, D., Chung, H., Cho, E., Kwon, Y., Jo, Y., & Choi, E. (2024) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 0

Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning

Wang, Z., Xu, C., Liu, B., Wang, Y., Han, S., Yao, Z., Yao, H., & He, Y. (2026) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 0

VIVID-10M: A Dataset and Baseline for Versatile and Interactive Video Local Editing

Hu, J., Zhong, T., Wang, X., Jiang, B., Tian, X., Yang, F., Wan, P., & Zhang, D. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 0

Harness-of-Harness: Multi-Day Autonomous Software Development with Continual Improvement

Yan, H., Su, M.-L., Zhang, H., Li, Z., Zhang, C., Zhang, S., Chen, Y., Bai, L., & Hu, S. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

MESH-Harness: Self-Improving Agent Harnesses via Bandit-Guided Compositional Evolution

Shang, Z., Huo, Y., Gong, M., Yan, A., Qu, Z., Dong, J., Low, B. K. H., Wu, C., & Dai, Z. (2026) · arXiv

Evolutionary Algorithms and ApplicationsAdvanced Bandit Algorithms Research

Cited by 0

When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents

Mishra, S., & Mishra, S. (2026) · arXiv

AI-based Problem Solving and PlanningTopic Modeling

Cited by 0

Do AI-Generated Pull Requests Get Rejected More? (Yes but Why?)

Wang, Y., & Yang, Z. (2026) · Proceedings of the 23rd International Conference on Mining Software Repositories

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

When Prompts Go Wrong: Evaluating Code Model Robustness to Ambiguous, Contradictory, and Incomplete Task Descriptions

Larbi, M., Akli, A., Papadakis, M., Bouyousfi, R., Cordy, M., Sarro, F., & Traon, Y. L. (2025) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 0

On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps

Heikkilä, M. A. (2024) · arXiv

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 0

Agentic Memory Management Is the Next Frontier of Information Retrieval

Ai, Q. (2026) · arXiv

Information Retrieval and Search BehaviorAI-based Problem Solving and Planning

Cited by 0

COLD: Causal reasOning in cLosed Daily activities

Joshi, A., Ahmad, A., & Modi, A. (2024) · arXiv

Context-Aware Activity Recognition SystemsLogic, Reasoning, and Knowledge

Cited by 0

Implicit Language Models are RNNs: Balancing Parallelization and Expressivity

Schöne, M., Rahmani, B., Kremer, H., Falck, F., Ballani, H., & Gladrow, J. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI

Lyu, B., Yang, Y., Huang, S., Zhang, J., Xu, Q., Li, X., Han, X., Zhang, Y., Zhang, H., Huang, R., et al. (2026) · arXiv

Artificial Intelligence ApplicationsMachine Learning and Data Classification

Cited by 0

Scaling Agent Learning via Experience Synthesis

Chen, Z., Zhao, Z., Zhang, K., Liu, B., Qi, Q., Wu, Y., Kalluri, T., Cao, S., Xiong, Y., Tong, H., et al. (2025) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 0

maars: Tidy Inference under the 'Models as Approximations' Framework in R

Fogliato, R., Shrotriya, S., & Kuchibhotla, A. K. (2021) · arXiv

Data Analysis with RAdvanced Statistical Methods and Models

Cited by 0

Multiqubit monogamy relations beyond shadow inequalities

Serrano-Ensástiga, E., Giraud, O., & Martin, J. (2026) · Physical Review A

Quantum Information and CryptographyQuantum Mechanics and Applications

Cited by 0