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data/retrieval_individual-76c7b5f4-5fbc-4311-bf05-8defcdc1ba4e.jsonl

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 {"tstamp": 1723013916.4093, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1723013913.9828, "finish": 1723013916.4093, "ip": "", "conv_id": "a397380963724fc587797870c0fbe369", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "How do I solve a 3x3x3 Rubik's cube?", "output": [["How do I solve a 3x3x3 Rubik's cube?", "Math Stackexchange\n\nQ: Can you compute the state of a 3x3x3 Rubik's cube if you only see three adjacent faces? I've learned from How many colors of a Rubik's Cube must be known to locate all? that you need to know a minimum of 17 stickers (spread across all its faces) for a 3x3x3 cube in order to compute its state, but if we just see three full adjacent faces and all the 27 stickers on those faces, can we always compute the cube state considering that the cube is always solvable?\n\nA: No.  To expand on @aschepler's excellent answer, consider\n$$\nF'L'(R^2URUR'U'R'U'R'UR')LF\n$$\n(the sequence in the parenthesis is just a standard edge switch).\nWhat you should have at the end of this algorithm is a cube that you can view from one angle that looks completely solved, but it isn't.\n"]], "corpus": "stackexchange"}
 {"tstamp": 1723014983.5091, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1723014981.384, "finish": 1723014983.5091, "ip": "", "conv_id": "0016f632f408472d8e569dd143bb3f80", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "Please review this as a test", "output": [["Please review this as a test", "Title: Do the Test Smells Assertion Roulette and Eager Test Impact Students' Troubleshooting and Debugging Capabilities?\n\nAbstract: To ensure the quality of a software system, developers perform an activity known as unit testing, where they write code (known as test cases) that verifies the individual software units that make up the system. Like production code, test cases are subject to bad programming practices, known as test smells, that hurt maintenance activities. An essential part of most maintenance activities is program comprehension which involves developers reading the code to understand its behavior to fix issues or update features. In this study, we conduct a controlled experiment with 96 undergraduate computer science students to investigate the impact of two common types of test smells, namely Assertion Roulette and Eager Test, on a student's ability to debug and troubleshoot test case failures. Our findings show that students take longer to correct errors in production code when smells are present in their associated test cases, especially Assertion Roulette. We envision our findings supporting academia in better equipping students with the knowledge and resources in writing and maintaining high-quality test cases. Our experimental materials are available online: https://wajdialjedaani.github.io/testsmellstd/"]], "corpus": "arxiv"}
 {"tstamp": 1723014983.5091, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1723014981.384, "finish": 1723014983.5091, "ip": "", "conv_id": "ab57ba3036a04a6b9e8c6196f436f849", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Please review this as a test", "output": [["Please review this as a test", "Title: Searching publications on software testing\n\nAbstract: This note concerns a search for publications in which the pragmatic concept of a test as conducted in the practice of software testing is formalized, a theory about software testing based on such a formalization is presented or it is demonstrated on the basis of such a theory that there are solid grounds to test software in cases where in principle other forms of analysis could be used. This note reports on the way in which the search has been carried out and the main outcomes of the search. The message of the note is that the fundamentals of software testing are not yet complete in some respects."]], "corpus": "arxiv"}
+{"tstamp": 1723015055.1262, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1723015053.0061, "finish": 1723015055.1262, "ip": "", "conv_id": "11214242c8574540955c3a781929000b", "model_name": "voyage-multilingual-2", "prompt": "Please find me newest papers on agentic frameworks", "output": [["Please find me newest papers on agentic frameworks", "Title: Agent-based computing from multi-agent systems to agent-based Models: a visual survey\n\nAbstract: Agent-Based Computing is a diverse research domain concerned with the building of intelligent software based on the concept of \"agents\". In this paper, we use Scientometric analysis to analyze all sub-domains of agent-based computing. Our data consists of 1,064 journal articles indexed in the ISI web of knowledge published during a twenty year period: 1990-2010. These were retrieved using a topic search with various keywords commonly used in sub-domains of agent-based computing. In our proposed approach, we have employed a combination of two applications for analysis, namely Network Workbench and CiteSpace - wherein Network Workbench allowed for the analysis of complex network aspects of the domain, detailed visualization-based analysis of the bibliographic data was performed using CiteSpace. Our results include the identification of the largest cluster based on keywords, the timeline of publication of index terms, the core journals and key subject categories. We also identify the core authors, top countries of origin of the manuscripts along with core research institutes. Finally, our results have interestingly revealed the strong presence of agent-based computing in a number of non-computing related scientific domains including Life Sciences, Ecological Sciences and Social Sciences."]], "corpus": "arxiv"}
+{"tstamp": 1723015055.1262, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723015053.0061, "finish": 1723015055.1262, "ip": "", "conv_id": "f20d2bd2a0cb458db92c2af60e3b5ea9", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Please find me newest papers on agentic frameworks", "output": [["Please find me newest papers on agentic frameworks", "Title: Analytic Deep Learning-based Surrogate Model for Operational Planning with Dynamic TTC Constraints\n\nAbstract: The increased penetration of wind power introduces more operational changes of critical corridors and the traditional time-consuming transient stability constrained total transfer capability (TTC) operational planning is unable to meet the real-time monitoring need. This paper develops a more computationally efficient approach to address that challenge via the analytical deep learning-based surrogate model. The key idea is to resort to the deep learning for developing a computationally cheap surrogate model to replace the original time-consuming differential-algebraic constraints related to TTC. However, the deep learning-based surrogate model introduces implicit rules that are difficult to handle in the optimization process. To this end, we derive the Jacobian and Hessian matrices of the implicit surrogate models and finally transfer them into an analytical formulation that can be easily solved by the interior point method. Surrogate modeling and problem reformulation allow us to achieve significantly improved computational efficiency and the yielded solutions can be used for operational planning. Numerical results carried out on the modified IEEE 39-bus system demonstrate the effectiveness of the proposed method in dealing with com-plicated TTC constraints while balancing the computational efficiency and accuracy."]], "corpus": "arxiv"}