:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autore principale:	Advani, Laksh
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2601.00513
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Trajectory Guard -- A Lightweight, Sequence-Aware Model for Real-Time Anomaly Detection in Agentic AI
di: Advani, Laksh
Pubblicazione: (2026)

Clever Materials: When Models Identify Good Materials for the Wrong Reasons
di: Jablonka, Kevin Maik
Pubblicazione: (2026)

Data Cartography for Detecting Memorization Hotspots and Guiding Data Interventions in Generative Models
di: Patel, Laksh, et al.
Pubblicazione: (2025)

Wrong Model, Right Uncertainty: Spatial Associations for Discrete Data with Misspecification
di: Burt, David R., et al.
Pubblicazione: (2025)

Perplexity Cannot Always Tell Right from Wrong
di: Veličković, Petar, et al.
Pubblicazione: (2026)

When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models
di: Guo, Zhixiang, et al.
Pubblicazione: (2026)

Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
di: Son, Seongho, et al.
Pubblicazione: (2024)

Stable but Wrong: When More Data Degrades Scientific Conclusions
di: Zhang, Zhipeng, et al.
Pubblicazione: (2026)

When to Trust the Cheap Check: Weak and Strong Verification for Reasoning
di: Kiyani, Shayan, et al.
Pubblicazione: (2026)

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
di: Wang, Sifan, et al.
Pubblicazione: (2026)

[Experiments & Analysis] Evaluating the Feasibility of Sampling-Based Techniques for Training Multilayer Perceptrons
di: Ebrahimi, Sana, et al.
Pubblicazione: (2023)

When LLMs Learn to Be Consistently Wrong: A Multi-Model Study of Linear Representations of Synthetic Deception
di: Zolfaghari, Vahideh
Pubblicazione: (2026)

Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents
di: Long, Carol Xuan
Pubblicazione: (2026)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
di: Singhi, Nishad, et al.
Pubblicazione: (2025)

Thinking Wrong in Silence: Backdoor Attacks on Continuous Latent Reasoning
di: Parekh, Swapnil
Pubblicazione: (2026)

Know When You're Wrong: Aligning Confidence with Correctness for LLM Error Detection
di: Xiaohu, Xie, et al.
Pubblicazione: (2026)

When Learning Rates Go Wrong: Early Structural Signals in PPO Actor-Critic
di: Fernández-Hernández, Alberto, et al.
Pubblicazione: (2026)

Acting for the Right Reasons: Creating Reason-Sensitive Artificial Moral Agents
di: Baum, Kevin, et al.
Pubblicazione: (2024)

Right for the Right Reasons: Avoiding Reasoning Shortcuts via Prototypical Neurosymbolic AI
di: Andolfi, Luca, et al.
Pubblicazione: (2025)

Towards Trustworthy GUI Agents: A Survey
di: Shi, Yucheng, et al.
Pubblicazione: (2025)

ThermEval: A Structured Benchmark for Evaluation of Vision-Language Models on Thermal Imagery
di: Shrivastava, Ayush, et al.
Pubblicazione: (2026)

Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL
di: Cai, Siyang, et al.
Pubblicazione: (2026)

Decidable By Construction: Design-Time Verification for Trustworthy AI
di: Haynes, Houston
Pubblicazione: (2026)

The Right Answer, the Wrong Direction: Why Transformers Fail at Counting and How to Fix It
di: Garcia, Gabriel
Pubblicazione: (2026)

All AI Models are Wrong, but Some are Optimal
di: Anand, Akhil S, et al.
Pubblicazione: (2025)

LLMs as Assessors: Right for the Right Reason?
di: Saha, Sourav, et al.
Pubblicazione: (2026)

VerificAgent: Domain-Specific Memory Verification for Scalable Oversight of Aligned Computer-Use Agents
di: Nguyen, Thong Q., et al.
Pubblicazione: (2025)

What is Wrong with Perplexity for Long-context Language Modeling?
di: Fang, Lizhe, et al.
Pubblicazione: (2024)

Beyond Benchmarks: Dynamic, Automatic And Systematic Red-Teaming Agents For Trustworthy Medical Language Models
di: Pan, Jiazhen, et al.
Pubblicazione: (2025)

Trustworthy Prediction with Gaussian Process Knowledge Scores
di: Butler, Kurt, et al.
Pubblicazione: (2025)

Verification and Validation for Trustworthy Scientific Machine Learning
di: Jakeman, John D., et al.
Pubblicazione: (2025)

Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision
di: Ning, Kanghui, et al.
Pubblicazione: (2025)

Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA
di: Martinez, John Ray B.
Pubblicazione: (2026)

An Accurate and Interpretable Framework for Trustworthy Process Monitoring
di: Wang, Hao, et al.
Pubblicazione: (2023)

ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations
di: Harit, Anoushka, et al.
Pubblicazione: (2025)

The Geometry of Self-Verification in a Task-Specific Reasoning Model
di: Lee, Andrew, et al.
Pubblicazione: (2025)

To Backtrack or Not to Backtrack: When Sequential Search Limits Model Reasoning
di: Qin, Tian, et al.
Pubblicazione: (2025)

Step-by-Step Diffusion: An Elementary Tutorial
di: Nakkiran, Preetum, et al.
Pubblicazione: (2024)

Out-of-Distribution Detection Methods Answer the Wrong Questions
di: Li, Yucen Lily, et al.
Pubblicazione: (2025)

Your Assumed DAG is Wrong and Here's How To Deal With It
di: Padh, Kirtan, et al.
Pubblicazione: (2025)