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data/retrieval_individual-8f49ab11-0eb0-4822-9300-c064e77ef34d.jsonl

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 {"tstamp": 1737721382.0739, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1737721379.8784, "finish": 1737721382.0739, "ip": "", "conv_id": "7fdcfc6f4e734f3d9cf4c392a5a5c835", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "Paper introducing ClimaX, a deep learning model that excels in diverse climate and weather tasks using self-supervised learning", "output": [["Paper introducing ClimaX, a deep learning model that excels in diverse climate and weather tasks using self-supervised learning", "Title: ClimaX: A foundation model for weather and climate\n\nAbstract: Most state-of-the-art approaches for weather and climate modeling are based on physics-informed numerical models of the atmosphere. These approaches aim to model the non-linear dynamics and complex interactions between multiple variables, which are challenging to approximate. Additionally, many such numerical models are computationally intensive, especially when modeling the atmospheric phenomenon at a fine-grained spatial and temporal resolution. Recent data-driven approaches based on machine learning instead aim to directly solve a downstream forecasting or projection task by learning a data-driven functional mapping using deep neural networks. However, these networks are trained using curated and homogeneous climate datasets for specific spatiotemporal tasks, and thus lack the generality of numerical models. We develop and demonstrate ClimaX, a flexible and generalizable deep learning model for weather and climate science that can be trained using heterogeneous datasets spanning different variables, spatio-temporal coverage, and physical groundings. ClimaX extends the Transformer architecture with novel encoding and aggregation blocks that allow effective use of available compute while maintaining general utility. ClimaX is pre-trained with a self-supervised learning objective on climate datasets derived from CMIP6. The pre-trained ClimaX can then be fine-tuned to address a breadth of climate and weather tasks, including those that involve atmospheric variables and spatio-temporal scales unseen during pretraining. Compared to existing data-driven baselines, we show that this generality in ClimaX results in superior performance on benchmarks for weather forecasting and climate projections, even when pretrained at lower resolutions and compute budgets. The source code is available at https://github.com/microsoft/ClimaX."]], "corpus": "arxiv"}
 {"tstamp": 1737721400.3398, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1737721398.134, "finish": 1737721400.3398, "ip": "", "conv_id": "33469fe07cff4d0bb1dd1a8b613c866d", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "who is openai ", "output": [["who is openai ", "Title: Dota 2 with Large Scale Deep Reinforcement Learning\n\nAbstract: On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game. The game of Dota 2 presents novel challenges for AI systems such as long time horizons, imperfect information, and complex, continuous state-action spaces, all challenges which will become increasingly central to more capable AI systems. OpenAI Five leveraged existing reinforcement learning techniques, scaled to learn from batches of approximately 2 million frames every 2 seconds. We developed a distributed training system and tools for continual training which allowed us to train OpenAI Five for 10 months. By defeating the Dota 2 world champion (Team OG), OpenAI Five demonstrates that self-play reinforcement learning can achieve superhuman performance on a difficult task."]], "corpus": "arxiv"}
 {"tstamp": 1737721400.3398, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1737721398.134, "finish": 1737721400.3398, "ip": "", "conv_id": "b7bc1cb8c0b8405ca3e5e61105273470", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "who is openai ", "output": [["who is openai ", "Title: ORRB -- OpenAI Remote Rendering Backend\n\nAbstract: We present the OpenAI Remote Rendering Backend (ORRB), a system that allows fast and customizable rendering of robotics environments. It is based on the Unity3d game engine and interfaces with the MuJoCo physics simulation library. ORRB was designed with visual domain randomization in mind. It is optimized for cloud deployment and high throughput operation. We are releasing it to the public under a liberal MIT license: https://github.com/openai/orrb ."]], "corpus": "arxiv"}
+{"tstamp": 1737724998.9429, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1737724996.79, "finish": 1737724998.9429, "ip": "", "conv_id": "fecc0d2aac8b4e8f8b898370086ef5d7", "model_name": "voyage-multilingual-2", "prompt": "A paper exploring the use of large language models like GPT-3 for hate speech detection.", "output": [["A paper exploring the use of large language models like GPT-3 for hate speech detection.", "Title: Detecting Hate Speech with GPT-3\n\nAbstract: Sophisticated language models such as OpenAI's GPT-3 can generate hateful text that targets marginalized groups. Given this capacity, we are interested in whether large language models can be used to identify hate speech and classify text as sexist or racist. We use GPT-3 to identify sexist and racist text passages with zero-, one-, and few-shot learning. We find that with zero- and one-shot learning, GPT-3 can identify sexist or racist text with an average accuracy between 55 per cent and 67 per cent, depending on the category of text and type of learning. With few-shot learning, the model's accuracy can be as high as 85 per cent. Large language models have a role to play in hate speech detection, and with further development they could eventually be used to counter hate speech."]], "corpus": "arxiv"}
+{"tstamp": 1737724998.9429, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1737724996.79, "finish": 1737724998.9429, "ip": "", "conv_id": "ad6fd3733e8e47db8d3444deb9f12820", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "A paper exploring the use of large language models like GPT-3 for hate speech detection.", "output": [["A paper exploring the use of large language models like GPT-3 for hate speech detection.", "Title: Quenched QCD near the chiral limit\n\nAbstract: A numerical study of quenched QCD for light quarks is presented using O(a) improved fermions. Particular attention is paid to the possible existence and determination of quenched chiral logarithms. A `safe' region to use for chiral extrapolations appears to be at and above the strange quark mass."]], "corpus": "arxiv"}
+{"tstamp": 1737725112.7341, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1737725112.5772, "finish": 1737725112.7341, "ip": "", "conv_id": "413cba4d53124b8490df08fa893afed0", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "who played bubba in the heat of the night", "output": [["who played bubba in the heat of the night", "Alan Autry\n\nCarlos Alan Autry Jr. (also known for a time as Carlos Brown; born July 31, 1952), is an American actor, politician, and former National Football League (NFL) player. During his brief football career, he was known as Carlos Brown.\nAutry played the role of Captain Bubba Skinner on the NBC, and later CBS, television drama series In the Heat of the Night, starring Carroll O'Connor. He has also appeared in films and other television shows. In November 2000, he was elected mayor of Fresno, California, and served for two four-year terms through January 2009.  From 2008 to 2011, Autry hosted a talk radio show on KYNO AM 940 in Fresno.  He now hosts a midday show on KXEX 1550 AM in Fresno.\nEarly life\nAutry was born in Shreveport, Louisiana, the son of Carl and Verna (née Brown) Autry. His name was changed to Carlos Brown when he was a year old, after his parents divorced. He worked alongside his mother and stepfather, Joe Duty, in California's San Joaquin Valley, where they planted and harvested cotton, grapes, and other crops, traveling around the valley living in migrant worker camps. When he was twelve, they settled in Riverdale, California."]], "corpus": "wikipedia"}

data/retrieval_single_choice-8f49ab11-0eb0-4822-9300-c064e77ef34d.jsonl

@@ -0,0 +1 @@
+{"tstamp": 1737725127.4518, "task_type": "retrieval", "type": "upvote", "models": "nomic-ai/nomic-embed-text-v1.5", "ip": "", "conv_id": "413cba4d53124b8490df08fa893afed0", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "who played bubba in the heat of the night", "output": [["who played bubba in the heat of the night", "Alan Autry\n\nCarlos Alan Autry Jr. (also known for a time as Carlos Brown; born July 31, 1952), is an American actor, politician, and former National Football League (NFL) player. During his brief football career, he was known as Carlos Brown.\nAutry played the role of Captain Bubba Skinner on the NBC, and later CBS, television drama series In the Heat of the Night, starring Carroll O'Connor. He has also appeared in films and other television shows. In November 2000, he was elected mayor of Fresno, California, and served for two four-year terms through January 2009.  From 2008 to 2011, Autry hosted a talk radio show on KYNO AM 940 in Fresno.  He now hosts a midday show on KXEX 1550 AM in Fresno.\nEarly life\nAutry was born in Shreveport, Louisiana, the son of Carl and Verna (née Brown) Autry. His name was changed to Carlos Brown when he was a year old, after his parents divorced. He worked alongside his mother and stepfather, Joe Duty, in California's San Joaquin Valley, where they planted and harvested cotton, grapes, and other crops, traveling around the valley living in migrant worker camps. When he was twelve, they settled in Riverdale, California."]], "corpus": "wikipedia"}