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data/retrieval_individual-f327ab98-e77d-487f-86d9-1e7eaaf8b6cc.jsonl

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 {"tstamp": 1728339652.0234, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1728339651.6991, "finish": 1728339652.0234, "ip": "", "conv_id": "d1393a6a3200459ab1257e4ec8baf351", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "do you capitalize y axis?", "output": [["do you capitalize y axis?", "Stackoverflow Stackexchange\n\nQ: how to convert 24-hour format TimeSpan to 12-hour format TimeSpan? I have TimeSpan data represented as 24-hour format, such as 14:00:00, I wanna convert it to 12-hour format, 2:00 PM, I googled and found something related in stackoverflow and msdn, but didn't solve this problem, can anyone help me? Thanks in advance.\nUpdate\nSeems that it's possible to convert 24-hour format TimeSpan to String, but impossible to convert the string to 12-hour format TimeSpan :(\nBut I still got SO MANY good answers, thanks!\n\nA: TimeSpan represents a time interval not a time of day. The DateTime structure is more likely what you're looking for.\n"]], "corpus": "stackexchange"}
 {"tstamp": 1728339696.4319, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1728339695.3318, "finish": 1728339696.4319, "ip": "", "conv_id": "6db949e7843e42609a724c1bd9e731ad", "model_name": "text-embedding-3-large", "prompt": "A unified automatic evaluation method for open-domain conversations with large language models", "output": [["A unified automatic evaluation method for open-domain conversations with large language models", "Title: LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models\n\nAbstract: We propose LLM-Eval, a unified multi-dimensional automatic evaluation method for open-domain conversations with large language models (LLMs). Existing evaluation methods often rely on human annotations, ground-truth responses, or multiple LLM prompts, which can be expensive and time-consuming. To address these issues, we design a single prompt-based evaluation method that leverages a unified evaluation schema to cover multiple dimensions of conversation quality in a single model call. We extensively evaluate the performance of LLM-Eval on various benchmark datasets, demonstrating its effectiveness, efficiency, and adaptability compared to state-of-the-art evaluation methods. Our analysis also highlights the importance of choosing suitable LLMs and decoding strategies for accurate evaluation results. LLM-Eval offers a versatile and robust solution for evaluating open-domain conversation systems, streamlining the evaluation process and providing consistent performance across diverse scenarios."]], "corpus": "arxiv"}
 {"tstamp": 1728339696.4319, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1728339695.3318, "finish": 1728339696.4319, "ip": "", "conv_id": "dbe46a1a12e24fbe82e420c87774451e", "model_name": "GritLM/GritLM-7B", "prompt": "A unified automatic evaluation method for open-domain conversations with large language models", "output": [["A unified automatic evaluation method for open-domain conversations with large language models", "Title: LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models\n\nAbstract: We propose LLM-Eval, a unified multi-dimensional automatic evaluation method for open-domain conversations with large language models (LLMs). Existing evaluation methods often rely on human annotations, ground-truth responses, or multiple LLM prompts, which can be expensive and time-consuming. To address these issues, we design a single prompt-based evaluation method that leverages a unified evaluation schema to cover multiple dimensions of conversation quality in a single model call. We extensively evaluate the performance of LLM-Eval on various benchmark datasets, demonstrating its effectiveness, efficiency, and adaptability compared to state-of-the-art evaluation methods. Our analysis also highlights the importance of choosing suitable LLMs and decoding strategies for accurate evaluation results. LLM-Eval offers a versatile and robust solution for evaluating open-domain conversation systems, streamlining the evaluation process and providing consistent performance across diverse scenarios."]], "corpus": "arxiv"}
+{"tstamp": 1728342716.2627, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1728342716.0512, "finish": 1728342716.2627, "ip": "", "conv_id": "9b2c31b0d44c4d3a97b052fa055acb98", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "why use ibgp and ospf?", "output": [["why use ibgp and ospf?", "Serverfault Stackexchange\n\nQ: What is the difference between OSPF and RIP? What is the difference between OSPF and RIP? Could someone explain the advantages and disadvantage？ Also when I should use one or the other.\n\nA: http://livinginternet.com/i/iw_route_igp_ospf.htm\nThe main difference between OSPF and RIP is that RIP only keeps track of the closest router for each destination address, while OSPF keeps track of a complete topological database of all connections in the local network.\nThis was the first search term google returned when I pasted your question there.\nTo more closely answer your question, if you're maintaing a very small network, RIP is fine, if you go beyond 3 or 4 routers then perhaps look at a more advanced routing protocol like OSPF.\n"]], "corpus": "stackexchange"}
+{"tstamp": 1728342716.2627, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1728342716.0512, "finish": 1728342716.2627, "ip": "", "conv_id": "62487a220ac94114876fc9c1f1db45cf", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "why use ibgp and ospf?", "output": [["why use ibgp and ospf?", "Serverfault Stackexchange\n\nQ: What is the difference between OSPF and RIP? What is the difference between OSPF and RIP? Could someone explain the advantages and disadvantage？ Also when I should use one or the other.\n\nA: http://livinginternet.com/i/iw_route_igp_ospf.htm\nThe main difference between OSPF and RIP is that RIP only keeps track of the closest router for each destination address, while OSPF keeps track of a complete topological database of all connections in the local network.\nThis was the first search term google returned when I pasted your question there.\nTo more closely answer your question, if you're maintaing a very small network, RIP is fine, if you go beyond 3 or 4 routers then perhaps look at a more advanced routing protocol like OSPF.\n"]], "corpus": "stackexchange"}