Guardado en:
| Autores principales: | Batth, Karmanbir, Sethi, Krish, Shariff, Aly, Shi, Leo, Patel, Hetul |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2504.17891 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Do We Really Even Need Data?
por: Hoffman, Kentaro, et al.
Publicado: (2024)
por: Hoffman, Kentaro, et al.
Publicado: (2024)
XGuardian: Towards Explainable and Generalized AI Anti-Cheat on FPS Games
por: Zhang, Jiayi, et al.
Publicado: (2026)
por: Zhang, Jiayi, et al.
Publicado: (2026)
Were RNNs All We Needed?
por: Feng, Leo, et al.
Publicado: (2024)
por: Feng, Leo, et al.
Publicado: (2024)
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
por: Tadigotla, Krish
Publicado: (2026)
por: Tadigotla, Krish
Publicado: (2026)
Agents Play Thousands of 3D Video Games
por: Xu, Zhongwen, et al.
Publicado: (2025)
por: Xu, Zhongwen, et al.
Publicado: (2025)
Why Do We Need Weight Decay in Modern Deep Learning?
por: D'Angelo, Francesco, et al.
Publicado: (2023)
por: D'Angelo, Francesco, et al.
Publicado: (2023)
From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs
por: Bhatnagar, Rohan, et al.
Publicado: (2025)
por: Bhatnagar, Rohan, et al.
Publicado: (2025)
Read to Play (R2-Play): Decision Transformer with Multimodal Game Instruction
por: Jin, Yonggang, et al.
Publicado: (2024)
por: Jin, Yonggang, et al.
Publicado: (2024)
Why Do We Need Warm-up? A Theoretical Perspective
por: Alimisis, Foivos, et al.
Publicado: (2025)
por: Alimisis, Foivos, et al.
Publicado: (2025)
Do We Need Frontier Models to Verify Mathematical Proofs?
por: Naik, Aaditya, et al.
Publicado: (2026)
por: Naik, Aaditya, et al.
Publicado: (2026)
Driving Privacy Forward: Mitigating Information Leakage within Smart Vehicles through Synthetic Data Generation
por: Parikh, Krish
Publicado: (2024)
por: Parikh, Krish
Publicado: (2024)
Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity
por: Ito, Akira, et al.
Publicado: (2025)
por: Ito, Akira, et al.
Publicado: (2025)
Do We Need Large VLMs for Spotting Soccer Actions?
por: Chakraborty, Ritabrata, et al.
Publicado: (2025)
por: Chakraborty, Ritabrata, et al.
Publicado: (2025)
MambaOut: Do We Really Need Mamba for Vision?
por: Yu, Weihao, et al.
Publicado: (2024)
por: Yu, Weihao, et al.
Publicado: (2024)
Learning to Play Video Games with Intuitive Physics Priors
por: Jaiswal, Abhishek, et al.
Publicado: (2024)
por: Jaiswal, Abhishek, et al.
Publicado: (2024)
Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
por: Mukherjee, Sagnik, et al.
Publicado: (2026)
por: Mukherjee, Sagnik, et al.
Publicado: (2026)
Do We Really Even Need Data? A Modern Look at Drawing Inference with Predicted Data
por: Salerno, Stephen, et al.
Publicado: (2025)
por: Salerno, Stephen, et al.
Publicado: (2025)
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
por: Wu, Xu, et al.
Publicado: (2025)
por: Wu, Xu, et al.
Publicado: (2025)
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
por: Teney, Damien, et al.
Publicado: (2025)
por: Teney, Damien, et al.
Publicado: (2025)
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
por: Fang, Minghong, et al.
Publicado: (2025)
por: Fang, Minghong, et al.
Publicado: (2025)
Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective
por: Jia, Zeyu, et al.
Publicado: (2025)
por: Jia, Zeyu, et al.
Publicado: (2025)
We Need to Rethink Benchmarking in Anomaly Detection
por: Röchner, Philipp, et al.
Publicado: (2025)
por: Röchner, Philipp, et al.
Publicado: (2025)
LLMs Will Always Hallucinate, and We Need to Live With This
por: Banerjee, Sourav, et al.
Publicado: (2024)
por: Banerjee, Sourav, et al.
Publicado: (2024)
Learning to play: A Multimodal Agent for 3D Game-Play
por: Yue, Yuguang, et al.
Publicado: (2025)
por: Yue, Yuguang, et al.
Publicado: (2025)
Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?
por: Zhao, Zijian, et al.
Publicado: (2025)
por: Zhao, Zijian, et al.
Publicado: (2025)
Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
por: Nguyen, Dang, et al.
Publicado: (2025)
por: Nguyen, Dang, et al.
Publicado: (2025)
DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
por: Naddeo, Kyle, et al.
Publicado: (2025)
por: Naddeo, Kyle, et al.
Publicado: (2025)
Inner Product Aware Quantization: Provably Fast, Accurate, and Adaptive Algorithms
por: White, Nathan, et al.
Publicado: (2026)
por: White, Nathan, et al.
Publicado: (2026)
A Survey of Explainable Reinforcement Learning: Targets, Methods and Needs
por: Saulières, Léo
Publicado: (2025)
por: Saulières, Léo
Publicado: (2025)
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
por: Zhang, Weizhi, et al.
Publicado: (2024)
por: Zhang, Weizhi, et al.
Publicado: (2024)
Playing Non-Embedded Card-Based Games with Reinforcement Learning
por: Wu, Tianyang, et al.
Publicado: (2025)
por: Wu, Tianyang, et al.
Publicado: (2025)
Mini-Game Lifetime Value Prediction in WeChat
por: Chen, Aochuan, et al.
Publicado: (2025)
por: Chen, Aochuan, et al.
Publicado: (2025)
Do We Really Need Quantum Machine Learning?: A Multidimensional Empirical Study
por: Vhaduri, Sudip, et al.
Publicado: (2026)
por: Vhaduri, Sudip, et al.
Publicado: (2026)
Learning Game-Playing Agents with Generative Code Optimization
por: Kuang, Zhiyi, et al.
Publicado: (2025)
por: Kuang, Zhiyi, et al.
Publicado: (2025)
Transforming Game Play: A Comparative Study of DCQN and DTQN Architectures in Reinforcement Learning
por: Stigall, William A.
Publicado: (2024)
por: Stigall, William A.
Publicado: (2024)
Position: We Need An Algorithmic Understanding of Generative AI
por: Eberle, Oliver, et al.
Publicado: (2025)
por: Eberle, Oliver, et al.
Publicado: (2025)
X-Node: Self-Explanation is All We Need
por: Sengupta, Prajit, et al.
Publicado: (2025)
por: Sengupta, Prajit, et al.
Publicado: (2025)
GD-FPS: Growth-Driven Feedforward Parameter Selection for Efficient Fine-Tuning
por: Yang, Kenneth, et al.
Publicado: (2025)
por: Yang, Kenneth, et al.
Publicado: (2025)
LayerCollapse: Adaptive compression of neural networks
por: Shabgahi, Soheil Zibakhsh, et al.
Publicado: (2023)
por: Shabgahi, Soheil Zibakhsh, et al.
Publicado: (2023)
Playing Markov Games Without Observing Payoffs
por: Ablin, Daniel, et al.
Publicado: (2025)
por: Ablin, Daniel, et al.
Publicado: (2025)
Ejemplares similares
-
Do We Really Even Need Data?
por: Hoffman, Kentaro, et al.
Publicado: (2024) -
XGuardian: Towards Explainable and Generalized AI Anti-Cheat on FPS Games
por: Zhang, Jiayi, et al.
Publicado: (2026) -
Were RNNs All We Needed?
por: Feng, Leo, et al.
Publicado: (2024) -
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
por: Tadigotla, Krish
Publicado: (2026) -
Agents Play Thousands of 3D Video Games
por: Xu, Zhongwen, et al.
Publicado: (2025)