IndustryLLM: Failure-Driven LLM Training for Industrial Procurement
cs.AI, cs.CL
Submitted: 2026-09-25
Updated: 2026-09-25
Terminology
Sources
- IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs
- Qwen3 Technical Report
- Gemma 3 Technical Report
- MedGemma Technical Report
- The Llama 3 Herd of Models
- DeepSeek-V3 Technical Report
- Intern-S1: A Scientific Multimodal Foundation Model
- Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
- MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Tulu 3: Pushing Frontiers in Open Language Model Post-Training
- Muon is Scalable for LLM Training
- Revisiting Pre-Trained Models for Chinese Natural Language Processing
- Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
- Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
- Adapting Large Language Models to Domains via Reading Comprehension
- Don't Stop Pretraining: Adapt Language Models to Domains and Tasks
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
- Improving language models by retrieving from trillions of tokens
- RAFT: Adapting Language Model to Domain Specific RAG
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