Saved in:
| Main Authors: | Batth, Karmanbir, Sethi, Krish, Shariff, Aly, Shi, Leo, Patel, Hetul |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.17891 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Do We Really Even Need Data?
by: Hoffman, Kentaro, et al.
Published: (2024)
by: Hoffman, Kentaro, et al.
Published: (2024)
XGuardian: Towards Explainable and Generalized AI Anti-Cheat on FPS Games
by: Zhang, Jiayi, et al.
Published: (2026)
by: Zhang, Jiayi, et al.
Published: (2026)
Were RNNs All We Needed?
by: Feng, Leo, et al.
Published: (2024)
by: Feng, Leo, et al.
Published: (2024)
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
by: Tadigotla, Krish
Published: (2026)
by: Tadigotla, Krish
Published: (2026)
Agents Play Thousands of 3D Video Games
by: Xu, Zhongwen, et al.
Published: (2025)
by: Xu, Zhongwen, et al.
Published: (2025)
Why Do We Need Weight Decay in Modern Deep Learning?
by: D'Angelo, Francesco, et al.
Published: (2023)
by: D'Angelo, Francesco, et al.
Published: (2023)
From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs
by: Bhatnagar, Rohan, et al.
Published: (2025)
by: Bhatnagar, Rohan, et al.
Published: (2025)
Read to Play (R2-Play): Decision Transformer with Multimodal Game Instruction
by: Jin, Yonggang, et al.
Published: (2024)
by: Jin, Yonggang, et al.
Published: (2024)
Why Do We Need Warm-up? A Theoretical Perspective
by: Alimisis, Foivos, et al.
Published: (2025)
by: Alimisis, Foivos, et al.
Published: (2025)
Do We Need Frontier Models to Verify Mathematical Proofs?
by: Naik, Aaditya, et al.
Published: (2026)
by: Naik, Aaditya, et al.
Published: (2026)
Driving Privacy Forward: Mitigating Information Leakage within Smart Vehicles through Synthetic Data Generation
by: Parikh, Krish
Published: (2024)
by: Parikh, Krish
Published: (2024)
Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity
by: Ito, Akira, et al.
Published: (2025)
by: Ito, Akira, et al.
Published: (2025)
Do We Need Large VLMs for Spotting Soccer Actions?
by: Chakraborty, Ritabrata, et al.
Published: (2025)
by: Chakraborty, Ritabrata, et al.
Published: (2025)
MambaOut: Do We Really Need Mamba for Vision?
by: Yu, Weihao, et al.
Published: (2024)
by: Yu, Weihao, et al.
Published: (2024)
Learning to Play Video Games with Intuitive Physics Priors
by: Jaiswal, Abhishek, et al.
Published: (2024)
by: Jaiswal, Abhishek, et al.
Published: (2024)
Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
by: Mukherjee, Sagnik, et al.
Published: (2026)
by: Mukherjee, Sagnik, et al.
Published: (2026)
Do We Really Even Need Data? A Modern Look at Drawing Inference with Predicted Data
by: Salerno, Stephen, et al.
Published: (2025)
by: Salerno, Stephen, et al.
Published: (2025)
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
by: Wu, Xu, et al.
Published: (2025)
by: Wu, Xu, et al.
Published: (2025)
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
by: Teney, Damien, et al.
Published: (2025)
by: Teney, Damien, et al.
Published: (2025)
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective
by: Jia, Zeyu, et al.
Published: (2025)
by: Jia, Zeyu, et al.
Published: (2025)
We Need to Rethink Benchmarking in Anomaly Detection
by: Röchner, Philipp, et al.
Published: (2025)
by: Röchner, Philipp, et al.
Published: (2025)
LLMs Will Always Hallucinate, and We Need to Live With This
by: Banerjee, Sourav, et al.
Published: (2024)
by: Banerjee, Sourav, et al.
Published: (2024)
Learning to play: A Multimodal Agent for 3D Game-Play
by: Yue, Yuguang, et al.
Published: (2025)
by: Yue, Yuguang, et al.
Published: (2025)
Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?
by: Zhao, Zijian, et al.
Published: (2025)
by: Zhao, Zijian, et al.
Published: (2025)
Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, et al.
Published: (2025)
DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
by: Naddeo, Kyle, et al.
Published: (2025)
by: Naddeo, Kyle, et al.
Published: (2025)
Inner Product Aware Quantization: Provably Fast, Accurate, and Adaptive Algorithms
by: White, Nathan, et al.
Published: (2026)
by: White, Nathan, et al.
Published: (2026)
A Survey of Explainable Reinforcement Learning: Targets, Methods and Needs
by: Saulières, Léo
Published: (2025)
by: Saulières, Léo
Published: (2025)
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
by: Zhang, Weizhi, et al.
Published: (2024)
by: Zhang, Weizhi, et al.
Published: (2024)
Playing Non-Embedded Card-Based Games with Reinforcement Learning
by: Wu, Tianyang, et al.
Published: (2025)
by: Wu, Tianyang, et al.
Published: (2025)
Mini-Game Lifetime Value Prediction in WeChat
by: Chen, Aochuan, et al.
Published: (2025)
by: Chen, Aochuan, et al.
Published: (2025)
Do We Really Need Quantum Machine Learning?: A Multidimensional Empirical Study
by: Vhaduri, Sudip, et al.
Published: (2026)
by: Vhaduri, Sudip, et al.
Published: (2026)
Learning Game-Playing Agents with Generative Code Optimization
by: Kuang, Zhiyi, et al.
Published: (2025)
by: Kuang, Zhiyi, et al.
Published: (2025)
Transforming Game Play: A Comparative Study of DCQN and DTQN Architectures in Reinforcement Learning
by: Stigall, William A.
Published: (2024)
by: Stigall, William A.
Published: (2024)
Position: We Need An Algorithmic Understanding of Generative AI
by: Eberle, Oliver, et al.
Published: (2025)
by: Eberle, Oliver, et al.
Published: (2025)
X-Node: Self-Explanation is All We Need
by: Sengupta, Prajit, et al.
Published: (2025)
by: Sengupta, Prajit, et al.
Published: (2025)
GD-FPS: Growth-Driven Feedforward Parameter Selection for Efficient Fine-Tuning
by: Yang, Kenneth, et al.
Published: (2025)
by: Yang, Kenneth, et al.
Published: (2025)
LayerCollapse: Adaptive compression of neural networks
by: Shabgahi, Soheil Zibakhsh, et al.
Published: (2023)
by: Shabgahi, Soheil Zibakhsh, et al.
Published: (2023)
Playing Markov Games Without Observing Payoffs
by: Ablin, Daniel, et al.
Published: (2025)
by: Ablin, Daniel, et al.
Published: (2025)
Similar Items
-
Do We Really Even Need Data?
by: Hoffman, Kentaro, et al.
Published: (2024) -
XGuardian: Towards Explainable and Generalized AI Anti-Cheat on FPS Games
by: Zhang, Jiayi, et al.
Published: (2026) -
Were RNNs All We Needed?
by: Feng, Leo, et al.
Published: (2024) -
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
by: Tadigotla, Krish
Published: (2026) -
Agents Play Thousands of 3D Video Games
by: Xu, Zhongwen, et al.
Published: (2025)