:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhang, Yichi, Seedat, Nabeel, Dong, Yinpeng, Cui, Peng, Zhu, Jun, van de Schaar, Mihaela
Formato:	Preprint
Publicado:	2026
Materias:	Artificial Intelligence Computation and Language
Acceso en línea:	https://arxiv.org/abs/2603.02798
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems
por: Seedat, Nabeel, et al.
Publicado: (2022)

You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling
por: Seedat, Nabeel, et al.
Publicado: (2024)

Large Language Models to Enhance Bayesian Optimization
por: Liu, Tennison, et al.
Publicado: (2024)

Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments
por: Rauba, Paulius, et al.
Publicado: (2024)

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
por: Seedat, Nabeel, et al.
Publicado: (2023)

When is Off-Policy Evaluation (Reward Modeling) Useful in Contextual Bandits? A Data-Centric Perspective
por: Sun, Hao, et al.
Publicado: (2023)

DAGnosis: Localized Identification of Data Inconsistencies using Structures
por: Huynh, Nicolas, et al.
Publicado: (2024)

Cascaded Language Models for Cost-effective Human-AI Decision-Making
por: Fanconi, Claudio, et al.
Publicado: (2025)

Matchmaker: Self-Improving Large Language Model Programs for Schema Matching
por: Seedat, Nabeel, et al.
Publicado: (2024)

Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
por: Saveliev, Evgeny S., et al.
Publicado: (2026)

Language Bottleneck Models for Qualitative Knowledge State Modeling
por: Berthon, Antonin, et al.
Publicado: (2025)

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities
por: Sun, Hao, et al.
Publicado: (2025)

To Whom Do Language Models Align? Measuring Principal Hierarchies Under High-Stakes Competing Demands
por: Yu, Fangyi, et al.
Publicado: (2026)

What's the next frontier for Data-centric AI? Data Savvy Agents
por: Seedat, Nabeel, et al.
Publicado: (2025)

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
por: Sun, Hao, et al.
Publicado: (2023)

RealSafe-R1: Safety-Aligned DeepSeek-R1 without Compromising Reasoning Capability
por: Zhang, Yichi, et al.
Publicado: (2025)

The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
por: Pouplin, Thomas, et al.
Publicado: (2024)

Beyond Pointwise Scores: Decomposed Criteria-Based Evaluation of LLM Responses
por: Yu, Fangyi, et al.
Publicado: (2025)

DeceptionBench: A Comprehensive Benchmark for AI Deception Behaviors in Real-world Scenarios
por: Huang, Yao, et al.
Publicado: (2025)

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
por: Seedat, Nabeel, et al.
Publicado: (2024)

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning
por: Liu, Tennison, et al.
Publicado: (2025)

RepoMirage: Probing Repository Context Reasoning in Code Agents with Perturbations
por: Li, Hanyu, et al.
Publicado: (2026)

Breaking the Ceiling: Exploring the Potential of Jailbreak Attacks through Expanding Strategy Space
por: Huang, Yao, et al.
Publicado: (2025)

Mitigating Overthinking in Large Reasoning Models via Manifold Steering
por: Huang, Yao, et al.
Publicado: (2025)

Active Task Disambiguation with LLMs
por: Kobalczyk, Katarzyna, et al.
Publicado: (2025)

TTPrint: Evidence-Grounded TTP Extraction via Diverge-then-Converge Verification
por: Cheng, Yutong, et al.
Publicado: (2026)

Towards Safe Reasoning in Large Reasoning Models via Corrective Intervention
por: Zhang, Yichi, et al.
Publicado: (2025)

A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents
por: Su, Hang, et al.
Publicado: (2025)

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs
por: Sun, Hao, et al.
Publicado: (2025)

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets
por: Zhang, Simpson, et al.
Publicado: (2025)

Strategic Self-Improvement for Competitive Agents in AI Labour Markets
por: Chiu, Christopher, et al.
Publicado: (2025)

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation
por: Zhang, Yichi, et al.
Publicado: (2025)

GameTalk: Training LLMs for Strategic Conversation
por: Vendrell, Victor Conchello, et al.
Publicado: (2026)

Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
por: Pouplin, Thomas, et al.
Publicado: (2024)

Implicit Behavioral Alignment of Language Agents in High-Stakes Crowd Simulations
por: Wang, Yunzhe, et al.
Publicado: (2025)

STAR-PólyaMath: Multi-Agent Reasoning under Persistent Meta-Strategic Supervision
por: Wu, Jiaao, et al.
Publicado: (2026)

Not All Explanations for Deep Learning Phenomena Are Equally Valuable
por: Jeffares, Alan, et al.
Publicado: (2025)

Preference Learning for AI Alignment: a Causal Perspective
por: Kobalczyk, Katarzyna, et al.
Publicado: (2025)

Active Timepoint Selection for Learning Measure-Valued Trajectories
por: Huynh, Nicolas, et al.
Publicado: (2026)

Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning
por: Sun, Hao, et al.
Publicado: (2024)