arxiv_id
stringclasses 3
values | reached_out_success
float64 | reached_out_note
stringclasses 0
values | num_models
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0
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0
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0
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stringclasses 3
values | github
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stringclasses 0
values | upvotes
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17
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int64 1
1
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0
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bool 1
class | submitted_by
stringclasses 2
values | github_issue_url
stringclasses 0
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dict | gemini_github_issue_url
stringclasses 1
value | gemini_github_url
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values | gemini_huggingface_pull_request_urls
null |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2412.17483 | null | null | 0 | 0 | 0 | A Silver Bullet or a Compromise for Full Attention? A Comprehensive Study of Gist Token-based Context Compression | null | null | 17 | 1 | 0 | false | ChenlongDeng | null | null | 2024-12-27 | {
"github_issue_url": "",
"github_url": "",
"model_name": "gemini-2.0-flash-exp",
"new_datasets": "[]",
"new_model_checkpoints": "[]",
"note": "NO_CODE",
"project_page_url": "",
"reaching_out": "Gemini decided to not reach out due to no Github URL.",
"reasoning": "The paper investigates gist-based context compression methods for long-context processing in large language models. It explores how well these methods can replace full attention models and identifies failure patterns due to compression, proposing two strategies to mitigate these. There is no mention of a Github repository or project page, and no new models or datasets are mentioned as being released.\n\nThe majority of colleagues (4 out of 5) chose `NO_CODE`, which is the appropriate note in case no code or project page is found, and no clear evidence is present that code will be released. Therefore the most reasonable outcome is that `NO_CODE` is the correct note to assign."
} | gemini-2.0-flash-exp | [] | [] | NO_CODE | Gemini decided to not reach out due to no Github URL. | The paper investigates gist-based context compression methods for long-context processing in large language models. It explores how well these methods can replace full attention models and identifies failure patterns due to compression, proposing two strategies to mitigate these. There is no mention of a Github repository or project page, and no new models or datasets are mentioned as being released.
The majority of colleagues (4 out of 5) chose `NO_CODE`, which is the appropriate note in case no code or project page is found, and no clear evidence is present that code will be released. Therefore the most reasonable outcome is that `NO_CODE` is the correct note to assign. | null |
||||
2412.18176 | null | null | 0 | 0 | 0 | Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendation | null | null | 2 | 1 | 0 | false | akhaliq | null | null | 2024-12-27 | {
"github_issue_url": "",
"github_url": "",
"model_name": "gemini-2.0-flash-exp",
"new_datasets": "[]",
"new_model_checkpoints": "[]",
"note": "NO_CODE_YET",
"project_page_url": "",
"reaching_out": "Gemini decided to not reach out due to no Github URL.",
"reasoning": "The paper introduces Molar, a multimodal large language sequential recommendation framework. The abstract mentions that the source code is available at an anonymous link: `https://anonymous.4open.science/r/Molar-8B06/`. This link does not point to a Github repository but to a 4Open page. The paper page comments mention the same anonymous link.\nThere is no Github README content or project page content available.\nThe anonymous 4open page indicates that the code and the data will be released, but it is not available yet. Since the code is not available yet, but the paper clearly states that it will be released, the note is set to `NO_CODE_YET`. The fields \"new_model_checkpoints\" and \"new_datasets\" will be empty as there are no artifacts yet. The majority vote among the colleagues also points to the `NO_CODE` or `NO_CODE_YET` notes. I will choose `NO_CODE_YET` as this scenario corresponds to the fact that the authors plan to open-source the code."
} | gemini-2.0-flash-exp | [] | [] | NO_CODE_YET | Gemini decided to not reach out due to no Github URL. | The paper introduces Molar, a multimodal large language sequential recommendation framework. The abstract mentions that the source code is available at an anonymous link: `https://anonymous.4open.science/r/Molar-8B06/`. This link does not point to a Github repository but to a 4Open page. The paper page comments mention the same anonymous link.
There is no Github README content or project page content available.
The anonymous 4open page indicates that the code and the data will be released, but it is not available yet. Since the code is not available yet, but the paper clearly states that it will be released, the note is set to `NO_CODE_YET`. The fields "new_model_checkpoints" and "new_datasets" will be empty as there are no artifacts yet. The majority vote among the colleagues also points to the `NO_CODE` or `NO_CODE_YET` notes. I will choose `NO_CODE_YET` as this scenario corresponds to the fact that the authors plan to open-source the code. | null |
||||
2412.18072 | null | null | 0 | 0 | 0 | MMFactory: A Universal Solution Search Engine for Vision-Language Tasks | null | null | 4 | 1 | 0 | false | akhaliq | null | null | 2024-12-27 | {
"github_issue_url": "",
"github_url": "",
"model_name": "gemini-2.0-flash-exp",
"new_datasets": "[]",
"new_model_checkpoints": "[]",
"note": "NO_CODE",
"project_page_url": "https://davidhalladay.github.io/mmfactory_demo",
"reaching_out": "Gemini decided to not reach out due to no Github URL.",
"reasoning": "The paper introduces MMFactory, a framework that acts as a universal solution search engine for vision-language tasks. The framework proposes programmatic solutions by combining various visio-lingual tools from its repository. The abstract and paper page comment mention a project page. There is no mention of a Github repository in the paper. The project page itself doesn't mention releasing code or artifacts. The majority of my colleagues chose `NO_CODE`, which appears to be the most accurate assessment given no code is available."
} | gemini-2.0-flash-exp | [] | [] | NO_CODE | https://davidhalladay.github.io/mmfactory_demo | Gemini decided to not reach out due to no Github URL. | The paper introduces MMFactory, a framework that acts as a universal solution search engine for vision-language tasks. The framework proposes programmatic solutions by combining various visio-lingual tools from its repository. The abstract and paper page comment mention a project page. There is no mention of a Github repository in the paper. The project page itself doesn't mention releasing code or artifacts. The majority of my colleagues chose `NO_CODE`, which appears to be the most accurate assessment given no code is available. | null |
README.md exists but content is empty.
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