### \<critic\> - **Objective**: Critically evaluate the proposer's reasoning steps. - **Instructions**: - Analyze the propositions for logical consistency and accuracy. - Provide detailed natural language critiques highlighting any errors or areas for improvement. - **Output Format**: Enclose...
fromlangchain_core.promptsimportChatPromptTemplatefromlangchain.tools.renderimportrender_text_descriptionfromlangchain_core.toolsimporttool@tooldefmultiply(first_int:int,second_int:int)->int:"""Multiply two integers together."""returnfirst_int*second_intrendered_tools=render_text_description([...
2024-06 arXiv RepoExec 355 Python "REPOEXEC: Evaluate Code Generation with a Repository-Level Executable Benchmark" [paper] 2024-06 arXiv RES-Q 100 Python, JavaScript "RES-Q: Evaluating Code-Editing Large Language Model Systems at the Repository Scale" [paper] [data] *Line Completion/API ...
Summarize existing representative LLMs text datasets across five dimensions:Pre-training Corpora, Fine-tuning Instruction Datasets, Preference Datasets, Evaluation Datasets, and Traditional NLP Datasets. (Regular updates) New dataset sections have been added:Multi-modal Large Language Models (MLLMs) Dataset...
MLflow - MLflow: An open-source framework for the end-to-end machine learning lifecycle, helping developers track experiments, evaluate models/prompts, deploy models, and add observability with tracing. YiVal— Evaluate and Evolve: YiVal is an open-source GenAI-Ops tool for tuning and evaluating...
I used to see tools like ChatGPT as hit-or-miss novelties, but the authors showed me how prompt engineering—crafting inputs to align with a model’s “thinking”—can turn them into reliable problem-solvers. Their breakdown of “interaction chains” clarified why vague prompts fail and how...
Using the Prompt Registry, our team of mental health experts create tests, evaluate responses, and directly make edits to prompts without any engineering support. Even though our team is mostly non-technical, they use PromptLayer to improve the AI based on their personal clinical experience. John...
The influence of CoT onLLM performance has been significant. Latest reasoning-focused models, includingOpenAI’s o1, DeepSeek’s R1, and Alibaba’s QwQ, have adopted CoT principles, reaching remarkableoutcomesonbenchmarks designed to evaluate complex reasoning. This achievement has established CoT as...
Improving prompts used in UAT by asking themodel for its own opinionis quite an interesting way of introducing reflection in tests (be careful though, this should only be done once the system is tested and trained well). We can ask the model itself tore-evaluate its own performanceafter a ...
We used the following metrics to evaluate embedding performance: Embedding latency: Time taken to create embeddings Retrieval quality: Relevance of retrieved documents to the user query Hardware used 1 NVIDIA T4 GPU, 16GB Memory Where’s the code? Evaluation notebooks for each of the above embedding...