Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)
Fuente:
arXiv
Saved in:
| Main Authors: | Lade, Ankit Hemant, Jasti, Sai Krishna, Kumar, Indar, Chadha, Aman |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PCA-Driven Adaptive Sensor Triage for Edge AI Inference
by: Lade, Ankit Hemant, et al.
Published: (2026)
by: Lade, Ankit Hemant, et al.
Published: (2026)
Supervised Dimensionality Reduction Revisited: Why LDA on Frozen CNN Features Deserves a Second Look
by: Kumar, Indar, et al.
Published: (2026)
by: Kumar, Indar, et al.
Published: (2026)
RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
by: Kumar, Indar, et al.
Published: (2026)
by: Kumar, Indar, et al.
Published: (2026)
Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting
by: Lade, Ankit, et al.
Published: (2026)
by: Lade, Ankit, et al.
Published: (2026)
Know What You Don't Know: Selective Prediction for Early Exit DNNs
by: Bajpai, Divya Jyoti, et al.
Published: (2025)
by: Bajpai, Divya Jyoti, et al.
Published: (2025)
What Do Latent Action Models Actually Learn?
by: Zhang, Chuheng, et al.
Published: (2025)
by: Zhang, Chuheng, et al.
Published: (2025)
Do's and Don'ts: Learning Desirable Skills with Instruction Videos
by: Kim, Hyunseung, et al.
Published: (2024)
by: Kim, Hyunseung, et al.
Published: (2024)
What LLMs Think When You Don't Tell Them What to Think About?
by: Kwon, Yongchan, et al.
Published: (2026)
by: Kwon, Yongchan, et al.
Published: (2026)
xAI-Drop: Don't Use What You Cannot Explain
by: De Luca, Vincenzo Marco, et al.
Published: (2024)
by: De Luca, Vincenzo Marco, et al.
Published: (2024)
Reasoning Models Don't Always Say What They Think
by: Chen, Yanda, et al.
Published: (2025)
by: Chen, Yanda, et al.
Published: (2025)
Know What You Don't Know: Uncertainty Calibration of Process Reward Models
by: Park, Young-Jin, et al.
Published: (2025)
by: Park, Young-Jin, et al.
Published: (2025)
Can Large Language Models Infer Causal Relationships from Real-World Text?
by: Saklad, Ryan, et al.
Published: (2025)
by: Saklad, Ryan, et al.
Published: (2025)
Discovering the Representation Bottleneck of Graph Neural Networks
by: Wu, Fang, et al.
Published: (2022)
by: Wu, Fang, et al.
Published: (2022)
Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds
by: Zhang, Jiefu, et al.
Published: (2026)
by: Zhang, Jiefu, et al.
Published: (2026)
Trust, or Don't Predict: Introducing the CWSA Family for Confidence-Aware Model Evaluation
by: Shahnazari, Kourosh, et al.
Published: (2025)
by: Shahnazari, Kourosh, et al.
Published: (2025)
Large Language Models Must Be Taught to Know What They Don't Know
by: Kapoor, Sanyam, et al.
Published: (2024)
by: Kapoor, Sanyam, et al.
Published: (2024)
What do Geometric Hallucination Detection Metrics Actually Measure?
by: Yeats, Eric, et al.
Published: (2026)
by: Yeats, Eric, et al.
Published: (2026)
Stroke Prediction using Clinical and Social Features in Machine Learning
by: Chadha, Aidan
Published: (2024)
by: Chadha, Aidan
Published: (2024)
Transformers Don't In-Context Learn Least Squares Regression
by: Hill, Joshua, et al.
Published: (2025)
by: Hill, Joshua, et al.
Published: (2025)
Benchmarking is Broken -- Don't Let AI be its Own Judge
by: Cheng, Zerui, et al.
Published: (2025)
by: Cheng, Zerui, et al.
Published: (2025)
Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning
by: Khoriaty, Matthew, et al.
Published: (2025)
by: Khoriaty, Matthew, et al.
Published: (2025)
Don't Waste Your Time: Early Stopping Cross-Validation
by: Bergman, Edward, et al.
Published: (2024)
by: Bergman, Edward, et al.
Published: (2024)
Causally Reliable Concept Bottleneck Models
by: De Felice, Giovanni, et al.
Published: (2025)
by: De Felice, Giovanni, et al.
Published: (2025)
AlignGuard-LoRA: Alignment-Preserving Fine-Tuning via Fisher-Guided Decomposition and Riemannian-Geodesic Collision Regularization
by: Das, Amitava, et al.
Published: (2025)
by: Das, Amitava, et al.
Published: (2025)
Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?
by: Sinha, Neelabh, et al.
Published: (2024)
by: Sinha, Neelabh, et al.
Published: (2024)
Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
by: Balne, Charith Chandra Sai, et al.
Published: (2024)
by: Balne, Charith Chandra Sai, et al.
Published: (2024)
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
by: Kazoom, Roie, et al.
Published: (2025)
by: Kazoom, Roie, et al.
Published: (2025)
Don't be lazy: CompleteP enables compute-efficient deep transformers
by: Dey, Nolan, et al.
Published: (2025)
by: Dey, Nolan, et al.
Published: (2025)
Causally-Aware Information Bottleneck for Domain Adaptation
by: Javidian, Mohammad Ali
Published: (2026)
by: Javidian, Mohammad Ali
Published: (2026)
Does Your Wildfire Prediction Model Actually Work, or Just Score Well?
by: Xu, Yangshuang, et al.
Published: (2026)
by: Xu, Yangshuang, et al.
Published: (2026)
mHC-lite: You Don't Need 20 Sinkhorn-Knopp Iterations
by: Yang, Yongyi, et al.
Published: (2026)
by: Yang, Yongyi, et al.
Published: (2026)
Don't throw the baby out with the bathwater: How and why deep learning for ARC
by: Cole, Jack, et al.
Published: (2025)
by: Cole, Jack, et al.
Published: (2025)
F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare
by: Plyusov, Daniil, et al.
Published: (2026)
by: Plyusov, Daniil, et al.
Published: (2026)
Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
by: Apicella, Andrea, et al.
Published: (2026)
by: Apicella, Andrea, et al.
Published: (2026)
Do Concept Bottleneck Models Respect Localities?
by: Raman, Naveen, et al.
Published: (2024)
by: Raman, Naveen, et al.
Published: (2024)
ECLIPTICA -- A Framework for Switchable LLM Alignment via CITA - Contrastive Instruction-Tuned Alignment
by: Wanaskar, Kapil, et al.
Published: (2026)
by: Wanaskar, Kapil, et al.
Published: (2026)
Don't Blind Your VLA: Aligning Visual Representations for OOD Generalization
by: Kachaev, Nikita, et al.
Published: (2025)
by: Kachaev, Nikita, et al.
Published: (2025)
Don't Let Bandit Feedback Pull Continual LLM-Recommender Updates Off Target
by: Kim, Taesan, et al.
Published: (2026)
by: Kim, Taesan, et al.
Published: (2026)
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
by: Sokar, Ghada, et al.
Published: (2024)
by: Sokar, Ghada, et al.
Published: (2024)
Angles Don't Lie: Unlocking Training-Efficient RL Through the Model's Own Signals
by: Wang, Qinsi, et al.
Published: (2025)
by: Wang, Qinsi, et al.
Published: (2025)
Similar Items
-
PCA-Driven Adaptive Sensor Triage for Edge AI Inference
by: Lade, Ankit Hemant, et al.
Published: (2026) -
Supervised Dimensionality Reduction Revisited: Why LDA on Frozen CNN Features Deserves a Second Look
by: Kumar, Indar, et al.
Published: (2026) -
RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
by: Kumar, Indar, et al.
Published: (2026) -
Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting
by: Lade, Ankit, et al.
Published: (2026) -
Know What You Don't Know: Selective Prediction for Early Exit DNNs
by: Bajpai, Divya Jyoti, et al.
Published: (2025)