·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Sony Music, Warner sue Anthropic, alleging a “brazen campaign” of intellectual property theft19h◆Sony Music and Warner Chappell are suing Anthropic19h◆“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z20h◆Nvidia’s AI advantage is moving beyond the GPU1d◆Musicians-turned-detectives are hunting for AI grifters1d◆Fine-Tuning of Transformer models with Frames1d◆Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection1d◆Naive Prompt Optimization: Rethinking the Need for Complex Prompt Search1d◆Syntax vs. Semantics: How Transformers Learn Deep Dependencies1d◆NeuronFuzz: Safety Neuron Guided Fuzzing for LLM Safety Evaluation1d◆FaulT-Bench: Towards Benchmarking Network Troubleshooting LLM Agents under Unreliable User Tickets1d◆Unsupervised Post-Training of Foundation Models: A Survey1d◆Drift-Adaptive ICU Intervention Prediction: Freezing the Physiological Encoder for Auditable Model Updating1d◆Jiuge-Tuiqiao: An Interpretable Human-AI System for Classical Chinese Poetry Refinement1d◆Is Your Neighborhood Safe? Place-based Stigma in Large Language Models' Urban Safety Judgments1d◆Magnon-induced phononic Chern insulator1d◆Five Primitives for Governing Autonomous AI Agents at Runtime1d◆AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design1d◆Categorizer Automata for Discounted-Sum Payoffs1d◆FIRSTPASS: A Multi-Domain, Multi-Round Peer Review Dataset Grounded in Real Editorial Outcomes1d◆Sony Music, Warner sue Anthropic, alleging a “brazen campaign” of intellectual property theft19h◆Sony Music and Warner Chappell are suing Anthropic19h◆“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z20h◆Nvidia’s AI advantage is moving beyond the GPU1d◆Musicians-turned-detectives are hunting for AI grifters1d◆Fine-Tuning of Transformer models with Frames1d◆Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection1d◆Naive Prompt Optimization: Rethinking the Need for Complex Prompt Search1d◆Syntax vs. Semantics: How Transformers Learn Deep Dependencies1d◆NeuronFuzz: Safety Neuron Guided Fuzzing for LLM Safety Evaluation1d◆FaulT-Bench: Towards Benchmarking Network Troubleshooting LLM Agents under Unreliable User Tickets1d◆Unsupervised Post-Training of Foundation Models: A Survey1d◆Drift-Adaptive ICU Intervention Prediction: Freezing the Physiological Encoder for Auditable Model Updating1d◆Jiuge-Tuiqiao: An Interpretable Human-AI System for Classical Chinese Poetry Refinement1d◆Is Your Neighborhood Safe? Place-based Stigma in Large Language Models' Urban Safety Judgments1d◆Magnon-induced phononic Chern insulator1d◆Five Primitives for Governing Autonomous AI Agents at Runtime1d◆AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design1d◆Categorizer Automata for Discounted-Sum Payoffs1d◆FIRSTPASS: A Multi-Domain, Multi-Round Peer Review Dataset Grounded in Real Editorial Outcomes1d◆
News/The Order Matters: Sequential Fine-Tuning of LLaMA for Coherent Automated Essay Scoring
arxiv
PublishedJune 10, 2026 at 4:00 AM

The Order Matters: Sequential Fine-Tuning of LLaMA for Coherent Automated Essay Scoring

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.10327v1 Announce Type: new Abstract: Automated Essay Scoring (AES) systems must judge interdependent discourse elements (e.g., lead, claim, evidence, conclusion), yet most approaches treat these in isolation, harming coherence and generalization. We investigate task-aware fine-tuning of L

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivFine-Tuning of Transformer models with Frames1darxivFeature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection1darxivNaive Prompt Optimization: Rethinking the Need for Complex Prompt Search1darxivSyntax vs. Semantics: How Transformers Learn Deep Dependencies1d
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews