:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Nahin, Shahriar Kabir, Xiao, Wenxiao, Liu, Joshua, Chhabra, Anshuman, Liu, Hongfu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.03950
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling
by: Monjur, Ocean, et al.
Published: (2026)

Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models
by: Nahin, Shahriar Kabir, et al.
Published: (2025)

Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis
by: Datta, Shrestha, et al.
Published: (2026)

Salutary Labeling with Zero Human Annotation
by: Xiao, Wenxiao, et al.
Published: (2024)

Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
by: Chhabra, Anshuman, et al.
Published: (2025)

SafeLens: Deliberate and Efficient Video Guardrails with Fast-and-Slow Screening
by: Nahin, Shahriar Kabir, et al.
Published: (2026)

Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models
by: Chhabra, Anshuman, et al.
Published: (2024)

First is Not Really Better Than Last: Evaluating Layer Choice and Aggregation Strategies in Language Model Data Influence Estimation
by: Vitel, Dmytro, et al.
Published: (2025)

Unraveling Indirect In-Context Learning Using Influence Functions
by: Askari, Hadi, et al.
Published: (2025)

LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions
by: Askari, Hadi, et al.
Published: (2025)

Revisit, Extend, and Enhance Hessian-Free Influence Functions
by: Yang, Ziao, et al.
Published: (2024)

Layer-Aware Influence for Online Data Valuation Estimation
by: Yang, Ziao, et al.
Published: (2025)

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
by: Amaefuna, Theophilus, et al.
Published: (2026)

Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers
by: Achara, Akshit, et al.
Published: (2025)

Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
by: Yao, Yihang, et al.
Published: (2026)

Fairness vs Performance: Characterizing the Pareto Frontier of Algorithmic Decision Systems
by: Wilms, Mieke, et al.
Published: (2026)

Federated Multi-Objective Learning with Controlled Pareto Frontiers
by: Rao, Jiansheng, et al.
Published: (2025)

Separation-Utility Pareto Frontier: An Information-Theoretic Characterization
by: Xu, Shizhou
Published: (2026)

Instance-Level Costs for Nuanced Classifier Evaluation
by: Kang, Kabir, et al.
Published: (2026)

ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers
by: Zhu, Ding, et al.
Published: (2024)

Neuroplasticity and Corruption in Model Mechanisms: A Case Study Of Indirect Object Identification
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)

On the transferability of Sparse Autoencoders for interpreting compressed models
by: Gupte, Suchit, et al.
Published: (2025)

BigMac: Breaking the Pareto Frontier of Compute and Memory in Multimodal LLM Training
by: Zhang, Zili, et al.
Published: (2026)

Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
by: Liu, Ziyi, et al.
Published: (2024)

The Pareto Frontier of Resilient Jet Tagging
by: Gambhir, Rikab, et al.
Published: (2025)

MPM-LLM4DSE: Reaching the Pareto Frontier in HLS with Multimodal Learning and LLM-Driven Exploration
by: Xu, Lei, et al.
Published: (2026)

Detecting Anomalies in Blockchain Transactions using Machine Learning Classifiers and Explainability Analysis
by: Hasan, Mohammad, et al.
Published: (2024)

No Certificate for Alignment: Two Independent Impossibilities and the Pareto Frontier of Achievable Safety Guarantees
by: Agarwal, Ayushi
Published: (2026)

Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search
by: Ma, Lianbo, et al.
Published: (2021)

What's In My Big Data?
by: Elazar, Yanai, et al.
Published: (2023)

Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies
by: Chalumeau, Felix, et al.
Published: (2025)

TransConv-DDPM: Enhanced Diffusion Model for Generating Time-Series Data in Healthcare
by: Kabir, Md Shahriar, et al.
Published: (2026)

What Does It Take to Build a Performant Selective Classifier?
by: Rabanser, Stephan, et al.
Published: (2025)

From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web
by: Prabhu, Ameya, et al.
Published: (2023)

AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models
by: Belay, Tadesse Destaw, et al.
Published: (2026)

COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier
by: Luo, Gaoxiang, et al.
Published: (2025)

Efficient Fairness-Performance Pareto Front Computation
by: Kozdoba, Mark, et al.
Published: (2024)

Advancing Test-Time Adaptation in Wild Acoustic Test Settings
by: Liu, Hongfu, et al.
Published: (2023)

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection
by: Zhang, Yunzhe, et al.
Published: (2026)

Delete My Account: Impact of Data Deletion on Machine Learning Classifiers
by: Dam, Tobias, et al.
Published: (2023)