#llmeval search results
I just asked my first prompt and voted on Codatta Arena! It is wild seeing how different top LLMs perform when you don’t know who’s answering. This is what real LLM evaluation should feel like. Go test it out: 👉 app.codatta.io/arena #CodattaArena #LLMEval @codatta_io
📊 Results? 🏆 General-Reasoner beats or matches GPT-4o on tough tests like: • MMLU-Pro • SuperGPQA • GPQA …and it still crushes math 🧮 #LLMeval #OpenSourceAI
LLM应用评估 传统的软件测试方法正在转向动态、情境敏感的Eval评估，以此应对大语言模型本身的输出非确定性，确保产品符合用户预期并稳定运行。 #llmeval #aiproduct #quality
Eval的出现和必要性 LLM应用开发的便捷性是一把双刃剑。虽然在演示中它可能表现优异，但生产环境的容错率却很低。 一个在沙盒环境中运行良好的提示词，可能会在实际场景的复杂性、用户多样性或边缘案例面前失效。 #llmeval #testing #llmproduct #quality #evals
3 Key Insights for AI Product Evals 🧩 When evaluating LLM models / products, keep in mind: - Eval solves real problems - Tools must FIT your needs - Ongoing process is critical #evals #llmeval #MLOps #genai
🚨 Many RAG systems fail silently: answers look fluent but aren’t grounded in the retrieved context. Faithfulness ≠ and Relevance both must be measured to build trust. Complete evaluation framework: tinyurl.com/2nxrard6 #RAG #LLMEval #Faithfulness
Your participation helps build the first transparent, community-driven benchmark for LLMs in Web3 — and your feedback directly shapes the future of AI research and development. Try it now and be part of this revolutionary shift: app.codatta.io/arena #LLMEval #AIResearch
Our new left nav is organized around these themes of #llmtracking and #llmeval. Within eval, find explainers on feedback functions, their definitions and how we test them. In tracking, check out new explainers on instrumentation and logging. And separated API refs for each.
• Vote for the better response, then reveal which models you just evaluated! 🔗 Experience a new level of LLM evaluation today: app.codatta.io/arena Your votes shape the future of AI. #LLMEval #AIResearch #TransparentAI #CodattaArena
Cast your vote, reveal the contenders and witness the raw essence of machine intellect unfold. Help shape a living, evolving benchmark for LLMs powered by Web3 and the wisdom of the crowd. Join now: app.codatta.io/arena #LLMEval #AIResearch #TransparentAI #CodattaArena
Gute Benchmarks messen reale Fähigkeiten – nicht nur Benchmark Scores. SWE-Bench zeigt, wie leicht Modelle optimiert, aber kaum generalisiert werden. Für LLMs im Codeeinsatz braucht es realitätsnahe Testszenarien, nicht nur Leaderboards. #LLMEval #LLMOps technologyreview.com/2025/05/08/111…
Teams are asking the right questions at #DataAISummit. See how Openlayer helps answer them. 📍 F624 #AIObservability #LLMEval #Openlayer
Fine-tuning isn’t just a technical step—it’s a strategic one. At @codatta_io, they help teams decide when to fine-tune, how to evaluate it, and what trade-offs to make for sustainable performance. Smart tuning = smarter agents. #Codatta #LLMeval #FineTuning
🚀 Today's Share: What You Need to Know About Fine-tuning Many people have been asking, "When should I use Fine-tuning?" 🧵Let’s break it down in simple terms 👇
LLM jury sounds like the next evolution in AI evaluation! 🧠🔍 Excited to see how ensembling multiple models can outperform a single judge. Checking out the tutorial! 🚀🔥 #AI #LLMEval
I asked ChatGPT to perform a dose conversion for a dangerous medication commonly used in the operating room. It was off by 7200%. This would be a fatal dose. #LLMeval #AIinMedicine #LLMsafety #benchmarks alx.gd/s0PY
Why does this matter? 🚀 Static benchmarks can be gamed—models memorize test data instead of truly learning. Agentic benchmarks force AI systems to demonstrate real-world capabilities by making decisions in complex, evolving scenarios. #AIResearch #LLMeval
Highly recommend for teams who want AI that’s not just functional — but impactful. 👉 maven.com/parlance-labs/… #AIEval #LLMEval #AIQA
Evaluators can hallucinate too. OffsetBias trains judges to see past style — and score for substance. By building contrastive control samples, it helps LLMs score outputs like humans do. aclanthology.org/2024.findings-… #LLMEval #AIBias #AlignmentTools
LLM Eval Harness – Meta-evaluation framework – Compare major models on standard tasks – Used by labs, researchers, and fine-tuners Not just scores. Meaningful deltas. #LLMeval #AIbenchmarks
🚨 Many RAG systems fail silently: answers look fluent but aren’t grounded in the retrieved context. Faithfulness ≠ and Relevance both must be measured to build trust. Complete evaluation framework: tinyurl.com/2nxrard6 #RAG #LLMEval #Faithfulness
Highly recommend for teams who want AI that’s not just functional — but impactful. 👉 maven.com/parlance-labs/… #AIEval #LLMEval #AIQA
LLM Eval Harness – Meta-evaluation framework – Compare major models on standard tasks – Used by labs, researchers, and fine-tuners Not just scores. Meaningful deltas. #LLMeval #AIbenchmarks
Teams are asking the right questions at #DataAISummit. See how Openlayer helps answer them. 📍 F624 #AIObservability #LLMEval #Openlayer
Want to know if your model is trustworthy? TrustLLM breaks it down: •Honesty •Helpfulness •Harmlessness •Fidelity GPT-4 still hallucinates. Claude 2 hedges. Gemini Pro hallucinates confidently. arxiv.org/abs/2401.05561 #TrustworthyAI #LLMEval #AIAlignment
Evaluators can hallucinate too. OffsetBias trains judges to see past style — and score for substance. By building contrastive control samples, it helps LLMs score outputs like humans do. aclanthology.org/2024.findings-… #LLMEval #AIBias #AlignmentTools
📊 Results? 🏆 General-Reasoner beats or matches GPT-4o on tough tests like: • MMLU-Pro • SuperGPQA • GPQA …and it still crushes math 🧮 #LLMeval #OpenSourceAI
Your participation helps build the first transparent, community-driven benchmark for LLMs in Web3 — and your feedback directly shapes the future of AI research and development. Try it now and be part of this revolutionary shift: app.codatta.io/arena #LLMEval #AIResearch
Gute Benchmarks messen reale Fähigkeiten – nicht nur Benchmark Scores. SWE-Bench zeigt, wie leicht Modelle optimiert, aber kaum generalisiert werden. Für LLMs im Codeeinsatz braucht es realitätsnahe Testszenarien, nicht nur Leaderboards. #LLMEval #LLMOps technologyreview.com/2025/05/08/111…
🧠 How do you really measure an LLM’s quality? No single benchmark is enough. Learn how to combine metrics, human feedback, and real-world signals to evaluate models the right way: labelyourdata.com/articles/llm-f… #LLM #LLMeval #LLMevaluation #ModelEvaluation
• Vote for the better response, then reveal which models you just evaluated! 🔗 Experience a new level of LLM evaluation today: app.codatta.io/arena Your votes shape the future of AI. #LLMEval #AIResearch #TransparentAI #CodattaArena
构建LLM评估的合成数据 Evidently的这个指南介绍如何搭建LLM测试数据集、利用合成数据生成基准真值数据集，以及测试集在RAG和AI智能体模拟中的应用方法 #LLM评估 #LLMeval #RAG #Agent
📌 In case you missed it A guide on creating LLM test datasets with synthetic data 🪄 The guide covers how to build LLM test datasets, how to use synthetic data for ground truth datasets, and how test datasets work for RAG and AI agent simulations 👇 evidentlyai.com/llm-guide/llm-…
I just asked my first prompt and voted on Codatta Arena! It is wild seeing how different top LLMs perform when you don’t know who’s answering. This is what real LLM evaluation should feel like. Go test it out: 👉 app.codatta.io/arena #CodattaArena #LLMEval @codatta_io
Codatta Arena is redefining LLM evaluation! Test top AI models, vote on the best responses, and help build a real-world benchmark in Web3. Try it now at Codatta Arena. #LLMEval #AIResearch #TransparentAI
LLM辅助评估 利用人工智能评估人工智能：通过一个大型语言模型对另一个模型的输出进行评价并提供解释说明。 这种评估方式的必要性在于：用户反馈或其他"真实依据"往往极其有限甚至完全缺失（即便能获取人工标注数据，成本依然高昂），且LLM应用本身极易变得复杂化。 #llmeval #evals
Eval的出现和必要性 LLM应用开发的便捷性是一把双刃剑。虽然在演示中它可能表现优异，但生产环境的容错率却很低。 一个在沙盒环境中运行良好的提示词，可能会在实际场景的复杂性、用户多样性或边缘案例面前失效。 #llmeval #testing #llmproduct #quality #evals
LLM应用评估 传统的软件测试方法正在转向动态、情境敏感的Eval评估，以此应对大语言模型本身的输出非确定性，确保产品符合用户预期并稳定运行。 #llmeval #aiproduct #quality
Fine-tuning isn’t just a technical step—it’s a strategic one. At @codatta_io, they help teams decide when to fine-tune, how to evaluate it, and what trade-offs to make for sustainable performance. Smart tuning = smarter agents. #Codatta #LLMeval #FineTuning
🚀 Today's Share: What You Need to Know About Fine-tuning Many people have been asking, "When should I use Fine-tuning?" 🧵Let’s break it down in simple terms 👇
📊 Results? 🏆 General-Reasoner beats or matches GPT-4o on tough tests like: • MMLU-Pro • SuperGPQA • GPQA …and it still crushes math 🧮 #LLMeval #OpenSourceAI
LLM应用评估 传统的软件测试方法正在转向动态、情境敏感的Eval评估，以此应对大语言模型本身的输出非确定性，确保产品符合用户预期并稳定运行。 #llmeval #aiproduct #quality
Eval的出现和必要性 LLM应用开发的便捷性是一把双刃剑。虽然在演示中它可能表现优异，但生产环境的容错率却很低。 一个在沙盒环境中运行良好的提示词，可能会在实际场景的复杂性、用户多样性或边缘案例面前失效。 #llmeval #testing #llmproduct #quality #evals
3 Key Insights for AI Product Evals 🧩 When evaluating LLM models / products, keep in mind: - Eval solves real problems - Tools must FIT your needs - Ongoing process is critical #evals #llmeval #MLOps #genai
Our new left nav is organized around these themes of #llmtracking and #llmeval. Within eval, find explainers on feedback functions, their definitions and how we test them. In tracking, check out new explainers on instrumentation and logging. And separated API refs for each.
I asked ChatGPT to perform a dose conversion for a dangerous medication commonly used in the operating room. It was off by 7200%. This would be a fatal dose. #LLMeval #AIinMedicine #LLMsafety #benchmarks alx.gd/s0PY
Discover the fast-growing leader in #LLMEvaluation and #LLMMonitoring! TruLens is skyrocketing with 8x its growth of just 3 months ago.🚀 Check it out here on GitHub: loom.ly/EtQQJ1Y #LLMeval #LLMobservability #LLMops #MLOps #AIQuality
🌟TruLens has over 100k downloads!🌟 Thanks to all of the LLM developers who trust us to eval their apps! 🙏 Need to test and track an LLM app? Check out TruLens. loom.ly/PBSsivc #LLMops #LLMeval #LLMapp #LLMdev #MLops
TruLens overview video! How you can use TruLens OSS to test & track your #LLMapp experiments. TruLens helps ensure better app performance, while minimizing risks like hallucinations and toxicity. New video from @datta_cs loom.ly/usWDoYw #LLMtesting #LLMeval #LLMstack
TruLens is the leading OSS #LLMeval library - over 1k downloads per day! If you've been testing your #LLMapp using "vibe check" it's time to upgrade to TruLens for #LLMappeval. Build better LLM apps, faster.🌟 Check it: loom.ly/PBSsivc #LLMtesting #LLMOps #MLOps #RAG
Excited to co-organize the HEAL workshop at @acm_chi 2025! HEAL addresses the "evaluation crisis" in LLM research and brings HCI and AI experts together to develop human-centered approaches to evaluating and auditing LLMs. 🔗 heal-workshop.github.io #NLProc #LLMeval #LLMsafety
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