Most cited papers
- Verified
Social Status and Anti-Immigrant Attitudes in Europe: An Examination from the Perspective of Social Dominance Theory
Küpper, B., Wolf, C., & Zick, A. (2010) · International Journal of Conflict and Violence (IJCV)
- Verified
Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Deng, Y., Zhang, W., Chen, Z., & Gu, Q. (2023) · arXiv
- Verified
CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environments
Huang, K.-H., Prabhakar, A., Dhawan, S., Mao, Y., Wang, H., Savarese, S., Xiong, C., Laban, P., & Wu, C.-S. (2024) · arXiv
- Verified
Redefining accountability: navigating legal challenges of participant liability in decentralized autonomous organizations
Napieralska, A., & Kępczyński, P. (2024) · arXiv
- Verified
Retrospective End-User Walkthrough: A Method for Assessing How People Combine Multiple AI Models in Decision-Making Systems
de Santana, V. F., Galeno, L. M. D. F., Brazil, E. V., Heching, A., & Cerqueira, R. (2023) · arXiv
- Verified
Information Seeking for Robust Decision Making under Partial Observability
Fang, D. C.-J., & Ke, T.-W. (2025) · arXiv
- Verified
The SmartSHARK Ecosystem for Software Repository Mining
Trautsch, A., Trautsch, F., Herbold, S., Ledel, B., & Grabowski, J. (2020) · arXiv
- Verified
UI-AGILE: Advancing GUI Agents with Effective Reinforcement Learning and Precise Inference-Time Grounding
Lian, S., Wu, Y., Ma, J., Ding, Y., Song, Z., Chen, B., Zheng, X., Li, H., & Ji, R. (2025) · arXiv
- Verified
A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future
Zhong, J., Shen, W., Li, Y., Gao, S., Lu, H., Chen, Y., Zhang, Y., Zhou, W., Gu, J., & Zou, L. (2025) · arXiv
- Verified
Are we measuring trust correctly in explainability, interpretability, and transparency research?
Miller, T. (2022) · arXiv
- Verified
MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition
Zhang, H., Zhuang, Z., Wang, X., Yang, X., & Zhang, Y. (2025) · arXiv
- Verified
Ultra-Sparse Memory Network
Huang, Z., Min, Q., Huang, H., Zhu, D., Zeng, Y., Guo, R., & Zhou, X. (2024) · arXiv
- Verified
Get Experience from Practice: LLM Agents with Record & Replay
Feng, E., Zhou, W., Liu, Z., Chen, L., Dong, Y., Zhang, C., Zhao, Y., Du, D., Hua, Z., Xia, Y., et al. (2025) · arXiv
- Verified
HCI Guidelines for Gender Equity and Inclusivity
Scheuerman, M. K., Spiel, K., Haimson, O. L., Hamidi, F., & Branham, S. M. (2020) · Maryland Shared Open Access Repository
- Verified
Step-by-Step Reasoning to Solve Grid Puzzles: Where do LLMs Falter?
Tyagi, N., Parmar, M., Kulkarni, M., RRV, A., Patel, N., Nakamura, M., Mitra, A., & Baral, C. (2024) · arXiv
- Verified
Deep ViT Features as Dense Visual Descriptors
Amir, S., Gandelsman, Y., Bagon, S., & Dekel, T. (2021) · arXiv
- Verified
When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI
Epstein, Z., Schroeder, H., & Newman, D. (2022) · arXiv
- Verified
Decision Transformer: Reinforcement Learning via Sequence Modeling
Chen, L., Lu, K., Rajeswaran, A., Lee, K., Grover, A., Laskin, M., Abbeel, P., Srinivas, A., & Mordatch, I. (2021) · arXiv
- Verified
Quark and Gluon Contents of a Lepton at High Energies
Han, T., Ma, Y., & Xie, K. (2021) · arXiv
- Verified
MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models
Yang, T., Shen, Z., Mi, Z., Zhang, Z., Zhou, J., Ji, J., Dai, J., Chen, J., Chen, B., & Yang, Y. (2026) · arXiv
- Verified
An active inference ontology for decentralized science: from situated sensemaking to the epistemic commons
Friedman, D., Applegate-Swanson, S., Balbuena, J. A., Choudhury, A., Cordes, R., El Damaty, S., Guénin—Carlut, A., Knight, V. B., Metelkin, I., Shrivastava, S., et al. (2022) · Zenodo
- Verified
Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents
Paglieri, D., Cupiał, B., Cook, J., Piterbarg, U., Tuyls, J., Grefenstette, E., Foerster, J. N., Parker-Holder, J., & Rocktäschel, T. (2025) · arXiv
- Verified
Multilingual E5 Text Embeddings: A Technical Report
Wang, L., Yang, N., Huang, X., Yang, L., Majumder, R., & Wei, F. (2024) · arXiv
- Verified
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
You, Y., Li, J., Reddi, S., Hseu, J., Kumar, S., Bhojanapalli, S., Song, X., Demmel, J., Keutzer, K., & Hsieh, C.-J. (2019) · arXiv
Go further with a free account
Verify every reference, keep papers in a library, and ask questions across them.
Sign up - it is free