Copertina

VMDT: Decoding the Trustworthiness of Video Foundation Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Potter, Yujin, Wang, Zhun, Crispino, Nicholas, Montgomery, Kyle, Xiong, Alexander, Chang, Ethan Y., Pinto, Francesco, Chen, Yuqi, Gupta, Rahul, Ziyadi, Morteza, Christodoulopoulos, Christos, Li, Bo, Wang, Chenguang, Song, Dawn
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Peer-Preservation in Frontier Models
di: Potter, Yujin, et al.
Pubblicazione: (2026)

Agent Instructs Large Language Models to be General Zero-Shot Reasoners
di: Crispino, Nicholas, et al.
Pubblicazione: (2023)

MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
di: Xu, Chejian, et al.
Pubblicazione: (2025)

A Framework for Formalizing LLM Agent Security
di: Siu, Vincent, et al.
Pubblicazione: (2026)

COSMIC: Generalized Refusal Direction Identification in LLM Activations
di: Siu, Vincent, et al.
Pubblicazione: (2025)

SteeringSafety: A Systematic Safety Evaluation Framework of Representation Steering in LLMs
di: Siu, Vincent, et al.
Pubblicazione: (2025)

Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning
di: Pasewark, Eric, et al.
Pubblicazione: (2024)

LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
di: Kolasani, Sai, et al.
Pubblicazione: (2025)

RepIt: Steering Language Models with Concept-Specific Refusal Vectors
di: Siu, Vincent, et al.
Pubblicazione: (2025)

Certifying Counterfactual Bias in LLMs
di: Chaudhary, Isha, et al.
Pubblicazione: (2024)

Predicting Task Performance with Context-aware Scaling Laws
di: Montgomery, Kyle, et al.
Pubblicazione: (2025)

Customize Multi-modal RAI Guardrails with Precedent-based predictions
di: Yang, Cheng-Fu, et al.
Pubblicazione: (2025)

Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A Pilot Study
di: Wang, Chenguang, et al.
Pubblicazione: (2024)

Budget-aware Test-time Scaling via Discriminative Verification
di: Montgomery, Kyle, et al.
Pubblicazione: (2025)

Partial Federated Learning
di: Feng, Tiantian, et al.
Pubblicazione: (2024)

Frontier AI's Impact on the Cybersecurity Landscape
di: Potter, Yujin, et al.
Pubblicazione: (2025)

Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis
di: Sharma, Tanusree, et al.
Pubblicazione: (2024)

InterPrior: Scaling Generative Control for Physics-Based Human-Object Interactions
di: Xu, Sirui, et al.
Pubblicazione: (2026)

Hidden Persuaders: LLMs' Political Leaning and Their Influence on Voters
di: Potter, Yujin, et al.
Pubblicazione: (2024)

Future of Algorithmic Organization: Large-Scale Analysis of Decentralized Autonomous Organizations (DAOs)
di: Sharma, Tanusree, et al.
Pubblicazione: (2024)

SoK: The Gap Between Data Rights Ideals and Reality
di: Potter, Yujin, et al.
Pubblicazione: (2023)

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
di: Wang, Boxin, et al.
Pubblicazione: (2023)

MLAN: Language-Based Instruction Tuning Preserves and Transfers Knowledge in Multimodal Language Models
di: Tu, Jianhong, et al.
Pubblicazione: (2024)

C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs
di: Gao, Rui, et al.
Pubblicazione: (2026)

AgentVigil: Generic Black-Box Red-teaming for Indirect Prompt Injection against LLM Agents
di: Wang, Zhun, et al.
Pubblicazione: (2025)

Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation
di: Lai, Shiyang, et al.
Pubblicazione: (2024)

OPTAGENT: Optimizing Multi-Agent LLM Interactions Through Verbal Reinforcement Learning for Enhanced Reasoning
di: Bi, Zhenyu, et al.
Pubblicazione: (2025)

JudgeBoard: Benchmarking and Enhancing Small Language Models for Reasoning Evaluation
di: Bi, Zhenyu, et al.
Pubblicazione: (2025)

SWAN: Semantic Watermarking with Abstract Meaning Representation
di: Ye, Ziping, et al.
Pubblicazione: (2026)

WebSentinel: Detecting and Localizing Prompt Injection Attacks for Web Agents
di: Wang, Xilong, et al.
Pubblicazione: (2026)

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
di: Hong, Junyuan, et al.
Pubblicazione: (2024)

PRINCIPIOS DE NEUROBIOLOGÍA
di: Luis Crispino
Pubblicazione: (2011)

BeyondBench: Contamination-Resistant Evaluation of Reasoning in Language Models
di: Srivastava, Gaurav, et al.
Pubblicazione: (2025)

RARE: Retrieval-Aware Robustness Evaluation for Retrieval-Augmented Generation Systems
di: Zeng, Yixiao, et al.
Pubblicazione: (2025)

The Media Specialist...Between A Rock and A Hard Place.
di: Heller, Dawn, Ed., et al.
Pubblicazione: (1978)

Harmonic LLMs are Trustworthy
di: Kersting, Nicholas S., et al.
Pubblicazione: (2024)

RAGPPI: RAG Benchmark for Protein-Protein Interactions in Drug Discovery
di: Jeon, Youngseung, et al.
Pubblicazione: (2025)

Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models
di: Wang, Hengyi, et al.
Pubblicazione: (2024)

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
di: Huang, Yue, et al.
Pubblicazione: (2025)

On the Foundations of Trustworthy Artificial Intelligence
di: Dunham, TJ
Pubblicazione: (2026)