Use `code` in your Markdown file.
",
+ "output": "\nTo convert the provided HTML snippet into Markdown format, you would handle it as follows:\n\nHTML:\n```html\nUse `code` in your Markdown file.
\n```\n\nMarkdown:\n```markdown\n`Use \\`code\\` in your Markdown file.`\n```\n\nIn Markdown, to represent inline code, you enclose the text in backticks (\\`\\`). Since the backtick character is used for this purpose, if you want to include an actual backtick within your inline code span, you need to escape it by using a backslash (\\). Thus, `\\`code\\`` in the Markdown version represents the inline code with the correct rendering of backticks.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Extract the method that has been used in the research from the abstract of the paper. Give the exact sentences from the abstract that discuss the method.\n\nWe present a state-of-the-art speech recognition system developed using end-to-end deep learning. Our architecture is significantly simpler than traditional speech systems, which rely on laboriously engineered processing pipelines; these traditional systems also tend to perform poorly when used in noisy environments. In contrast, our system does not need hand-designed components to model background noise, reverberation, or speaker variation, but instead directly learns a function that is robust to such effects. We do not need a phoneme dictionary, nor even the concept of a \"phoneme.\" Key to our approach is a well-optimized RNN training system that uses multiple GPUs, as well as a set of novel data synthesis techniques that allow us to efficiently obtain a large amount of varied data for training. Our system, called Deep Speech, outperforms previously published results on the widely studied Switchboard Hub5'00, achieving 16.0% error on the full test set. Deep Speech also handles challenging noisy environments better than widely used, state-of-the-art commercial speech systems.Collapse",
+ "output": "\nThe method used in the research is explicitly mentioned in the following sentences from the abstract:\n\n1. \"Our architecture is significantly simpler than traditional speech systems, which rely on laboriously engineered processing pipelines...\"\n2. \"our system directly learns a function that is robust to such effects [background noise, reverberation, or speaker variation].\"\n3. \"Key to our approach is a well-optimized RNN training system that uses multiple GPUs...\"\n4. \"as well as a set of novel data synthesis techniques that allow us to efficiently obtain a large amount of varied data for training.\"\n\nThese sentences outline the methodology employed in developing the Deep Speech system, highlighting its end-to-end deep learning approach, simplicity compared to traditional systems, the use of a well-optimized RNN (Recurrent Neural Network) training system with multiple GPUs for processing power, and the application of novel data synthesis techniques for training with diverse data.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "You need to come up with the names of some of the papers that relate to the paper you are given.\n\nRoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering",
+ "output": "\nCreating the names of related papers can be a creative process that reflects the themes, focus, and contributions of the original work. Given the title of your paper, \"RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering,\" here are some suggestions for related paper titles that revolve around similar themes of robustness, multi-evidence utilization, and multi-answer QA systems. These titles can help you identify or create a coherent body of research that explores various aspects of this domain:\n\n1. \"Advancing Robustness in Question Answering Systems: Methods and Challenges\"\n2. \"The Role of Multi-evidence Fusion in Enhancing Question Answering Accuracy\"\n3. \"Towards Understanding Multi-answer Question Answering: A Survey\"\n4. \"Building Resilient QA Systems: Strategies for Handling Ambiguity and Variability\"\n5. \"Incorporating Diverse Evidence Sources for Improved Machine Comprehension\"\n6. \"Evaluating the Robustness of Automated Question Answering: Beyond Single-answer Paradigms\"\n7. \"Cross-lingual Challenges in Multi-evidence, Multi-answer Question Answering Systems\"\n8. \"Deep Learning Approaches for Robust Multi-evidence Information Processing in QA Systems\"\n9. \"Designing Benchmarks for Assessing the Robustness of Multi-answer QA Systems\"\n10. \"From Single to Multi: Transitioning Question Answering Towards Multi-evidence, Multi-answer Paradigms\"\n\nThese titles are crafted to reflect the core themes of your original paper, making them potentially relevant and complementary in your research area. They span a range of topics from methodological advancements and challenges, to surveys, evaluations, and benchmark creations, which are essential for progressing the field of robust, multi-evidence, multi-answer question answering.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Create a short, concise summary of the paper based on its abstract.\n\nFew-shot learning (FSL) is one of the key future steps in machine learning and raises a lot of attention. In this paper, we focus on the FSL problem of dialogue understanding, which contains two closely related tasks: intent detection and slot filling. Dialogue understanding has been proven to benefit a lot from jointly learning the two sub-tasks. However, such joint learning becomes challenging in the few-shot scenarios: on the one hand, the sparsity of samples greatly magnifies the difficulty of modeling the connection between the two tasks; on the other hand, how to jointly learn multiple tasks in the few-shot setting is still less investigated. In response to this, we introduce FewJoint, the first FSL benchmark for joint dialogue understanding. FewJoint provides a new corpus with 59 different dialogue domains from real industrial API and a code platform to ease FSL experiment set-up, which are expected to advance the research of this field. Further, we find that insufficient performance of the few-shot setting often leads to noisy sharing between two sub-task and disturbs joint learning. To tackle this, we guide slot with explicit intent information and propose a novel trust gating mechanism that blocks low-confidence intent information to ensure high quality sharing. Besides, we introduce a Reptile-based meta-learning strategy to achieve better generalization in unseen few-shot domains. In the experiments, the proposed method brings significant improvements on two datasets and achieve new state-of-the-art performance.",
+ "output": "\n**Summary: FewJoint - Advancing Few-Shot Learning in Dialogue Understanding**\n\nThis paper introduces FewJoint, a pioneering benchmark designed to tackle the few-shot learning (FSL) challenges in joint dialogue understanding, encompassing intent detection and slot filling tasks. Highlighting the significance of modeling the connection between these tasks, the paper notes the challenges in few-shot scenarios, including sample sparsity and the under-explored area of joint multi-task learning. FewJoint addresses these challenges through a novel approach:\n\n1. **Benchmark and Corpus:** A new corpus featuring 59 diverse dialogue domains from real-world industrial APIs, along with a coding platform for streamlined FSL experimentation.\n \n2. **Methodological Innovations:** Identifies the issue of suboptimal performance in FSL leading to poor task sharing. Proposes solutions:\n - **Trust Gating Mechanism:** Implements a gatekeeping function that blocks low-confidence intent information, ensuring more reliable information sharing between tasks.\n - **Meta-Learning Strategy:** Utilizes a Reptile-based strategy to enhance the model's generalization capabilities in unseen few-shot domains.\n\n3. **Experimental Results:** Demonstrates significant performance improvements over existing methods on two datasets, setting new state-of-the-art benchmarks.\n\n**FewJoint** contributes to the advancement of few-shot learning in complex dialogue understanding tasks, offering a robust framework for future research and applications in machine learning.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "You will need to compose the ABC notation for a given song.\n\nThe South Wind",
+ "output": "\nComposing ABC notation for a song involves translating its melody into a specific symbolic representation used by those interested in folk music and traditional tunes. ABC notation uses a series of letters, numbers, and symbols to denote pitch, duration, and other musical elements. Given the song \"The South Wind,\" which is a traditional tune often played in Irish and Scottish music sessions, here's a simplified example of how you might start to notate it. Keep in mind that ABC notation can vary slightly in its exact representation depending on the transcriber's interpretation of the tune.\n\n```\nX: 1\nT: The South Wind\nK: G\nM: 4/4\nL: 1/4\nQ:1/4=120\nV: V1 treble\n||:G2 GAG|B2 BAB:|\n||:d2 ded|c2 cec:|\n||:e2 efg|a2 afd|\n||:g2 gfg|e2 egd:|\n||:G2 GAG|B2 BAB:|\n||:d2 ded|c2 cec:|\n||:e2 efg|a2 afd|\n||:g2 gfg|e2 egd:|\n||:G2 G4|B2 B2:|\n||:d4 d2|c2 c2:|\n||:e2 e2|f2 f2:|\n||:g2 g2|a2 a2:|\n||:G2 G4|B2 B2:|\n||:d4 d2|c2 c2:|\n||:e2 e2|f2 f2:|\n||:g2 g2|a2 a2:|\nX: 2\nK: G\nV: V2 bass\n||:G,2 G,A,|B,2 B,A,:|\n||:d',2 d',e',|c',2 c',e',:|\n||:e',2 e',f',|a',2 a',f',:|\n||:g',2 g',f',|e',2 e',d':|\n||:G,2 G,A,|B,2 B,A,:|\n||:d',2 d',e',|c',2 c',e',:|\n||:e',2 e',f',|a',2 a',f',:|\n||:g',2 g',f',|e',2 e',d':|\n||:G,2 G,4|B,2 B,,2:|\n||:d',4 d',2|c',2 c',2:|\n||:e',2 e',2|f',2 f',2:|\n||:g',2 g',2|a',2 a',2:|\n||:G,2 G,4|B,2 B,,2:|\n||:d',4 d',2|c',2 c',2:|\n||:e',2 e',2|f',2 f',2:|\n||:g',2 g',2|a',2 a',2:|\n```\n\nThis is a basic representation. The \"V:\" line indicates which voice part the following notes will be for (treble or bass). The \"K:\" line specifies the key in which the tune is played, and the \"M:\" line indicates the meter. The tempo is suggested with \"Q:\" where \"1/4=120\" implies the quarter note equals 120 beats per minute. Each bar of music is separated by \"||:\", and the notes are represented by the letters corresponding to the notes on a standard keyboard (G=G, A=A, B=B, etc.), with numbers indicating the octave (,2 for an octave lower, ,4 for two octaves lower, etc.). The comma after a note indicates the note is held for its full duration; in this case, the half note.\n\nRemember, ABC notation is a tool for conveying the essence of a melody and can vary depending on the transcriber's interpretation. It's also important to note that this is a simplified version meant for educational purposes and may not capture all the nuances and variations of \"The South Wind.\"\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Categorize the given magazine based on its content into one of the categories: Politics, Entertainment News, Tech News, Business News, Parenting & Kids, Health & Healing, Cooking, Food & Wine, and Arts & Literature,\n\nInc.",
+ "output": "\nBased on the information provided in the name \"Inc.\", the magazine is most likely focused on business-related content. Therefore, the appropriate category for this magazine would be **Business News**. This category is fitting as magazines like \"Inc.\" typically cover topics such as entrepreneurship, business strategies, startup reviews, industry insights, and leadership advice, catering to business owners, entrepreneurs, and professionals seeking to stay updated on the latest trends and news in the business world.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Decide if the given email belongs to the Promotions or Social category.\n\nSubject: You have an invitation\nEmail: Hi, I'd like to join your LinkedIn network.",
+ "output": "\nBased on the information provided in the email subject and content, it's more aligned with the **Social Category**. Here's a breakdown of the reasoning:\n\n- **Subject (\"You have an invitation\"):** This line suggests a personal or networking-related invitation, which is more of a social interaction rather than a promotional offer.\n- **Content (\"Hi, I'd like to join your LinkedIn network.\"):** This statement explicitly indicates a request to connect on LinkedIn, which is a professional networking platform. It's a social action where someone wants to expand their professional network, not a promotional solicitation for a product, service, or event.\n\nTherefore, categorizing this email under Social is more appropriate given its focus on networking and personal connection rather than promoting something.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "The story of a movie has been described using many emojis. You need to guess the name of the movie based on the emojis.\n\n🧙♂️🚪📚🦅⚡",
+ "output": "\nBased on the emojis provided, it seems we're piecing together a description related to a well-known story that involves a young wizard, magical elements, and a distinctive creature. The emojis are:\n\n🧙♂️ - Typically represents a wizard.\n🚪 - Could indicate a door or entrance, often significant in stories involving magical worlds or hidden places.\n📚 - Represents books, a common element in stories featuring magic, learning, or knowledge.\n🦅 - The eagle, which in many narratives symbolizes courage, wisdom, or a messenger.\n⚡ - Traditionally represents lightning, associated with power, electricity, or, in the context of a famous story, a distinctive magical spell.\n\nPutting these clues together, the movie (or story) described is likely \"Harry Potter.\" The series famously follows a young wizard, Harry Potter, who attends Hogwarts School of Witchcraft and Wizardry. The elements mentioned (a wizard, a door possibly hinting at the hidden platform 9¾, books as a common sight in a school of magic, an eagle which is the emblem of the Gryffindor house, and a lightning symbol often associated with Harry Potter himself due to his distinctive scar) all align with elements known from J.K. Rowling's famous series. Therefore, the most fitting guess for the movie described by these emojis is \"Harry Potter.\"\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Come up with an interesting idea for a new movie plot. Your plot should be described with a title and a summary.",
+ "output": "\n### Title: **Echoes of Tomorrow**\n\n### Summary:\n\nIn the dystopian future of 2145, humanity is on the brink of extinction due to catastrophic climate change and resource depletion. Society is fragmented, with the remnants of humanity living in fortified cities, barely surviving. Amidst this bleak landscape emerges a technological breakthrough - the Chronoscope, a device capable of viewing alternative realities and past timelines. \n\nThe protagonist, Dr. Lena Hart, a brilliant but disillusioned physicist, discovers that the Chronoscope holds the key to altering past events, potentially reshaping the future. However, her research is heavily monitored by the authoritarian government, which sees the device as a tool for maintaining control rather than as a means to save humanity.\n\nHaunted by a personal tragedy that unfolded in the current dire state of the world, Lena embarks on a secret mission to pilot the Chronoscope beyond its intended viewing capabilities, aiming to intervene in pivotal moments that led to the Earth's decline. Her journey through time is not without risks; altering the past could have unforeseen consequences, creating a paradox that might erase her very existence or worse, exacerbate the timeline's dystopian reality.\n\nAs Lena delves deeper into the past, she uncovers a global conspiracy involving the current government, revealing that their actions had been instrumental in hastening the Earth's demise. With the help of a rogue AI named Echo, who was once the personal assistant to a key figure in the events she's trying to change, Lena must navigate a labyrinth of ethical dilemmas, political intrigue, and personal redemption.\n\n**Echoes of Tomorrow** is a thrilling, thought-provoking sci-fi film that explores themes of destiny, the power of choice, and the responsibility inherent in possessing the ability to change history. As Lena races against time to avert disaster, she must confront her own beliefs about the nature of time and the true cost of saving the future. The movie culminates in a climactic showdown between Lena and the forces attempting to control time, leading to a conclusion that challenges the audience's perception of endings and beginnings, and the impact of individual actions on the course of human history.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Change the first person to the third person in the given sentence. The meaning should be kept, but you can paraphrase it or expand it in order to have a better pose.\n\nWe were recently able to increase the amount of stock we hold with the same supplier thereby reducing our risk.",
+ "output": "\nThey were recently able to increase the amount of stock held with the same supplier, thereby diminishing their risk.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "You should capitalize the sentence according to the guide.\n\nGuide: Every other letter alternates between lower case and upper case.\nSentence: A giant spider blocks your path.",
+ "output": "\nFollowing the provided guide, which instructs to alternate every other letter between lower case and upper case, the capitalized sentence of \"A giant spider blocks your path\" would look like this:\n\n**A GIANT SPIDER BLOCKS YOUR PATH.**\n\nThis application follows the alternating case pattern starting from the first letter.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Create alliterations by finding synonyms for words in the given sentence.\n\nDavid wears a hat everyday.",
+ "output": "\nCreating alliterations involves the use of words that start with the same sound or letter to enhance the rhythm and mood of a phrase. To craft an alliterative sentence based on the original statement \"David wears a hat every day,\" we can find synonyms that not only convey the same meaning but also share the same initial sound. Here's how the sentence could be transformed:\n\n1. **David Donates Dapper Apparel**: \n - **David**: Remains the same as it's the subject's name.\n - **Donates**: A synonym for \"wears\" could be \"donates\" if we're creative, suggesting a contribution to a style or cause rather than the act of wearing per se.\n - **Dapper**: A synonym for \"a hat,\" meaning stylishly dressed or neat, can also refer to the hat itself, suggesting style.\n - **Apparel**: A synonym for \"hat,\" though more broad, can fit the alliteration if we're stretching the definition to include headwear in a stylish sense.\n\n Resulting Alliterative Sentence: \"David donates dapper apparel daily.\"\n\n2. **Dapper David Dons Daily Decorations**:\n - **Dapper David**: Retains alliteration with \"David\" and adds \"dapper\" to describe him, suggesting style.\n - **Dons**: Another synonym for \"wears,\" indicating the act of putting on.\n - **Daily Decorations**: Here, \"daily\" maintains the frequency from the original sentence, and \"decorations\" serves as a synonym for \"hat,\" implying something that adorns or decorates his outfit daily.\n\n Resulting Alliterative Sentence: \"Dapper David dons daily decorations.\"\n\nThese examples play with the original sentence to create alliterations while trying to maintain the core meaning. The choice of synonyms allows for creative expression while adhering to the alliterative technique.\n",
+ "generator": "Nanbeige-Plus-Chat-v0.1",
+ "dataset": "selfinstruct"
+ },
+ {
+ "instruction": "Convert the given description to a bash command.\n\nread the first 10 lines from f",
+ "output": "\nTo convert the description \"read the first 10 lines from file 'f'\" into a bash command, you would use the `head` command in Unix/Linux. The `head` command is used to output the beginning part of a file. By default, `head` outputs the first 10 lines of the file, but you can specify a different number using the `-n` option.\n\nHere is how you would write the command:\n\n```bash\nhead -n 10 f\n```\n\nThis command will read and display the first 10 lines from the file named 'f'. If the file is named differently, replace 'f' with the correct filename. Make sure that the file is in the current directory or provide the full path to the file.\n\nHere is a breakdown of the command:\n\n- `head`: This is the command used to output the beginning of a file.\n- `-n 10`: This option specifies that you want the first 10 lines. The `-n` followed by a number is used to limit the output to that number of lines.\n- `f`: This is the filename from which you want to read the lines. Ensure it is either in the current directory or provide the correct path.\n\nRemember, in Unix-like systems, you can usually determine the command options by typing `man Here is a picture of a beautiful sunset:
\n\n\n