惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

U
Unit 42
V
V2EX
Martin Fowler
Martin Fowler
博客园 - Franky
P
Proofpoint News Feed
P
Palo Alto Networks Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
B
Blog
The Register - Security
The Register - Security
Latest news
Latest news
S
Security @ Cisco Blogs
Simon Willison's Weblog
Simon Willison's Weblog
Recorded Future
Recorded Future
大猫的无限游戏
大猫的无限游戏
M
Microsoft Research Blog - Microsoft Research
Scott Helme
Scott Helme
T
Tailwind CSS Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
True Tiger Recordings
有赞技术团队
有赞技术团队
I
Intezer
Cisco Talos Blog
Cisco Talos Blog
Hacker News - Newest:
Hacker News - Newest: "LLM"
The GitHub Blog
The GitHub Blog
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
T
Tenable Blog
博客园 - 叶小钗
Hugging Face - Blog
Hugging Face - Blog
Hacker News: Ask HN
Hacker News: Ask HN
S
Security Archives - TechRepublic
F
Future of Privacy Forum
爱范儿
爱范儿
PCI Perspectives
PCI Perspectives
H
Help Net Security
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
T
The Blog of Author Tim Ferriss
MyScale Blog
MyScale Blog
N
Netflix TechBlog - Medium
罗磊的独立博客
Apple Machine Learning Research
Apple Machine Learning Research
MongoDB | Blog
MongoDB | Blog
Security Latest
Security Latest
美团技术团队
博客园 - 三生石上(FineUI控件)
S
Schneier on Security
量子位
C
CERT Recently Published Vulnerability Notes
SecWiki News
SecWiki News

cs.LG updates on arXiv.org

AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks $\textit{BlockFormer}$ : Transformer-based inference from interaction maps Provable Joint Decontamination for Benchmarking Multiple Large Language Models One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation What are the Right Symmetries for Formal Theorem Proving? stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation Bandit Convex Optimization with Gradient Prediction Adaptivity Symbolic Density Estimation for Discrete Distributions Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs Alike Parts: A Feature-Informed Approach to Local and Global Prototype Explanations I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching Aerodynamic force reconstruction using physics-informed Gaussian processes Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series Dynamic Mixture of Latent Memories for Self-Evolving Agents One-Way Policy Optimization for Self-Evolving LLMs LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring Calibration, Uncertainty Communication, and Deployment Readiness in CKD Risk Prediction: A Framework Evaluation Study Same Architecture, Different Capacity: Optimizer-Induced Spectral Scaling Laws Noise Schedule Design for Diffusion Models: An Optimal Control Perspective Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs When to Switch, Not Just What: Transition Quality Prediction in Clash Royale Tabular foundation models for robust calibration of near-infrared chemical sensing data No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Well-Tempered Metadynamics Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy Toward Understanding Adversarial Distillation: Why Robust Teachers Fail From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs Learning Causal Orderings for In-Context Tabular Prediction An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification Riemannian geometry meets fMRI: the advantages of modeling correlation manifolds and eigenvector subspaces DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes Can Transformers Learn to Verify During Backtracking Search? Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification Detecting Atypical Clients in Federated Learning via Representation-Level Divergence A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos Manifold-Guided Attention Steering Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization How Many Different Outputs Can a Transformer Generate? CausalGuard: Conformal Inference under Graph Uncertainty How Sparsity Allocation Shapes Label-Free Post-Pruning Recoverability IKNO: Infinite-order Kernel Neural Operators AgForce Enables Antigen-conditioned Generative Antibody Design Long-term Fairness with Selective Labels Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-Dimensional Control Tasks Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems Double descent for least-squares interpolation on contaminated data: A simulation study Predicting Performance of Symbolic and Prompt Programs with Examples The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity Harnesses for Inference-Time Alignment over Execution Trajectories Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning Physics-Informed Generative Solver: Bridging Data-Driven Priors and Conservation Laws for Stable Spatiotemporal Field Reconstruction Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability Machine learning prediction of obstructive coronary artery disease using opportunistic coronary calcium and epicardial fat assessments from CT calcium scoring scans Three Costs of Amortizing Gaussian Process Inference with Neural Processes MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery VeriScale: Adversarial Test-Suite Scaling for Verifiable Code Generation
Exploring the Effectiveness of Using LLMs for Automated Assessment of Student Self Explanations in Programming Education
Arun-Balajie · 2026-05-23 · via cs.LG updates on arXiv.org

View PDF HTML (experimental)

Abstract:Worked examples are step-by-step solutions to problems in a specific domain, offered to students to acquire domain-specific problem-solving skills. The effectiveness of worked examples could be enhanced by combining them with self-explanations, which ask students to explain rather than passively study each problem-solving step. The main challenge of this approach is assessing the correctness of the student's explanations. In the prevailing approach, student explanations are judged by their semantic similarity to an instructor's or domain expert's explanation. Given recent advances in LLM-based automated scoring, it remains unclear whether semantic similarity methods are still the most effective technique to automatically score textual student responses like essays or code explanations. Comparing these methods also requires quality datasets that offer distinctive features such as balanced class distributions and domain-specific labeled data for automated scoring tasks. In this paper, we present a rigorous comparison between LLMs and semantic similarity used for automated scoring, framed as a binary classification task.
Subjects: Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
Cite as: arXiv:2605.21614 [cs.HC]
  (or arXiv:2605.21614v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2605.21614

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Arun Balajiee Lekshmi Narayanan [view email]
[v1] Wed, 20 May 2026 18:22:22 UTC (341 KB)