{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/gpt/papers/8","list_of":"/method/gpt","method":"GPT","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":8,"pages_in_order":13,"rows_per_page":100,"rows":[701,800],"of":1212,"counts":{"archive_papers_tagged":1212,"with_a_code_link":453,"where_syntology_ran_a_sample":152,"not_listed_spam_title":0,"listed":1212,"listed_where_code_ran":152,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":130,"every_run_a_failure_of_syntologys_instrument":22,"listed_with_a_run_with_no_instrument_failure":130,"listed_every_run_a_failure_of_syntologys_instrument":22,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/gpt","prev":"/method/gpt/papers/7","next":"/method/gpt/papers/9","papers":[{"paper":null,"slug":"generative-linguistic-representation-for","title":"Generative linguistic representation for spoken language identification","date":"2023-12-18","arxiv_id":"2312.10964","n_code_links":0,"syntology":null},{"paper":null,"slug":"artificial-intelligence-optical-hardware","title":"Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s","date":"2023-12-17","arxiv_id":"2312.10639","n_code_links":0,"syntology":null},{"paper":"/paper/decoding-concerns-multi-label-classification","slug":"decoding-concerns-multi-label-classification","title":"Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social Media","date":"2023-12-17","arxiv_id":"2312.10626","n_code_links":1,"syntology":null},{"paper":null,"slug":"t2m-hifigpt-generating-high-quality-human","title":"T2M-HiFiGPT: Generating High Quality Human Motion from Textual Descriptions with Residual Discrete Representations","date":"2023-12-17","arxiv_id":"2312.10628","n_code_links":0,"syntology":null},{"paper":null,"slug":"red-ai-inconsistent-responses-from-gpt3-5","title":"Red AI? Inconsistent Responses from GPT3.5 Models on Political Issues in the US and China","date":"2023-12-15","arxiv_id":"2312.09917","n_code_links":0,"syntology":null},{"paper":null,"slug":"motion-flow-matching-for-human-motion","title":"Motion Flow Matching for Human Motion Synthesis and Editing","date":"2023-12-14","arxiv_id":"2312.08895","n_code_links":0,"syntology":null},{"paper":"/paper/causality-analysis-for-evaluating-the","slug":"causality-analysis-for-evaluating-the","title":"Causality Analysis for Evaluating the Security of Large Language Models","date":"2023-12-13","arxiv_id":"2312.07876","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":6,"n_instrument":1,"unverified":2,"pointer_only":9,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["casperllm/casper"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"large-language-models-are-complex-table","title":"Large Language Models are Complex Table Parsers","date":"2023-12-13","arxiv_id":"2312.11521","n_code_links":0,"syntology":null},{"paper":null,"slug":"native-language-identification-with-large","title":"Native Language Identification with Large Language Models","date":"2023-12-13","arxiv_id":"2312.07819","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-large-language-models-to-facilitate","title":"Exploring Large Language Models to Facilitate Variable Autonomy for Human-Robot Teaming","date":"2023-12-12","arxiv_id":"2312.07214","n_code_links":0,"syntology":null},{"paper":null,"slug":"sm70-a-large-language-model-for-medical","title":"SM70: A Large Language Model for Medical Devices","date":"2023-12-12","arxiv_id":"2312.06974","n_code_links":0,"syntology":null},{"paper":null,"slug":"survey-on-foundation-models-for-prognostics","title":"Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems","date":"2023-12-11","arxiv_id":"2312.06261","n_code_links":0,"syntology":null},{"paper":null,"slug":"early-chatgpt-user-portrait-through-the-lens","title":"Early ChatGPT User Portrait through the Lens of Data","date":"2023-12-10","arxiv_id":"2312.10078","n_code_links":0,"syntology":null},{"paper":"/paper/sim-gpt-text-similarity-via-gpt-annotated","slug":"sim-gpt-text-similarity-via-gpt-annotated","title":"Sim-GPT: Text Similarity via GPT Annotated Data","date":"2023-12-09","arxiv_id":"2312.05603","n_code_links":1,"syntology":null},{"paper":null,"slug":"make-them-spill-the-beans-coercive-knowledge","title":"Make Them Spill the Beans! Coercive Knowledge Extraction from (Production) LLMs","date":"2023-12-08","arxiv_id":"2312.04782","n_code_links":0,"syntology":null},{"paper":null,"slug":"prospective-role-of-foundation-models-in","title":"Prospective Role of Foundation Models in Advancing Autonomous Vehicles","date":"2023-12-08","arxiv_id":"2405.02288","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-sarcasm-detection-with-openai-gpt-based","title":"On Sarcasm Detection with OpenAI GPT-based Models","date":"2023-12-07","arxiv_id":"2312.04642","n_code_links":0,"syntology":null},{"paper":null,"slug":"purple-llama-cyberseceval-a-secure-coding","title":"Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models","date":"2023-12-07","arxiv_id":"2312.04724","n_code_links":0,"syntology":null},{"paper":"/paper/not-all-large-language-models-llms-succumb-to","slug":"not-all-large-language-models-llms-succumb-to","title":"Exploring the Reversal Curse and Other Deductive Logical Reasoning in BERT and GPT-Based Large Language Models","date":"2023-12-06","arxiv_id":"2312.03633","n_code_links":1,"syntology":null},{"paper":null,"slug":"rank-without-gpt-building-gpt-independent","title":"Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models","date":"2023-12-05","arxiv_id":"2312.02969","n_code_links":0,"syntology":null},{"paper":null,"slug":"jellyfish-a-large-language-model-for-data","title":"Jellyfish: A Large Language Model for Data Preprocessing","date":"2023-12-04","arxiv_id":"2312.01678","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-are-zero-shot-text","slug":"large-language-models-are-zero-shot-text","title":"Large Language Models Are Zero-Shot Text Classifiers","date":"2023-12-02","arxiv_id":"2312.01044","n_code_links":1,"syntology":null},{"paper":"/paper/gift-generative-interpretable-fine-tuning","slug":"gift-generative-interpretable-fine-tuning","title":"Generative Parameter-Efficient Fine-Tuning","date":"2023-12-01","arxiv_id":"2312.00700","n_code_links":1,"syntology":{"ran":12,"of":16,"n_ran_checked":12,"n_instrument":0,"unverified":4,"pointer_only":10,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["savadikarc/gift"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"applying-large-language-models-and-chain-of","title":"Applying Large Language Models and Chain-of-Thought for Automatic Scoring","date":"2023-11-30","arxiv_id":"2312.03748","n_code_links":0,"syntology":null},{"paper":null,"slug":"iag-induction-augmented-generation-framework","title":"IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions","date":"2023-11-30","arxiv_id":"2311.18397","n_code_links":0,"syntology":null},{"paper":"/paper/biomedical-knowledge-graph-enhanced-prompt","slug":"biomedical-knowledge-graph-enhanced-prompt","title":"Biomedical knowledge graph-optimized prompt generation for large language models","date":"2023-11-29","arxiv_id":"2311.17330","n_code_links":1,"syntology":{"ran":0,"of":3,"n_ran_checked":0,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"0 ran · 3 unverified","official":{"repos":["BaranziniLab/KG_RAG"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"paper":null,"slug":"improving-the-robustness-of-transformer-based","title":"Improving the Robustness of Transformer-based Large Language Models with Dynamic Attention","date":"2023-11-29","arxiv_id":"2311.17400","n_code_links":0,"syntology":null},{"paper":null,"slug":"timelygpt-recurrent-convolutional-transformer","title":"TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare","date":"2023-11-29","arxiv_id":"2312.00817","n_code_links":0,"syntology":null},{"paper":"/paper/characterglm-customizing-chinese","slug":"characterglm-customizing-chinese","title":"CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models","date":"2023-11-28","arxiv_id":"2311.16832","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["thu-coai/characterglm-6b"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/chatgpt-s-one-year-anniversary-are-open","slug":"chatgpt-s-one-year-anniversary-are-open","title":"ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?","date":"2023-11-28","arxiv_id":"2311.16989","n_code_links":1,"syntology":null},{"paper":null,"slug":"cole-a-hierarchical-generation-framework-for","title":"COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design","date":"2023-11-28","arxiv_id":"2311.16974","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparing-generative-chatbots-based-on","title":"Comparing Generative Chatbots Based on Process Requirements","date":"2023-11-28","arxiv_id":"2312.03741","n_code_links":0,"syntology":null},{"paper":"/paper/seed-bench-2-benchmarking-multimodal-large","slug":"seed-bench-2-benchmarking-multimodal-large","title":"SEED-Bench-2: Benchmarking Multimodal Large Language Models","date":"2023-11-28","arxiv_id":"2311.17092","n_code_links":2,"syntology":null},{"paper":null,"slug":"real-customization-or-just-marketing-are","title":"Real Customization or Just Marketing: Are Customized Versions of Chat GPT Useful?","date":"2023-11-27","arxiv_id":"2312.03728","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-ai-derived-data-for-carbon","title":"Leveraging AI-derived Data for Carbon Accounting: Information Extraction from Alternative Sources","date":"2023-11-26","arxiv_id":"2312.03722","n_code_links":0,"syntology":null},{"paper":"/paper/uhgeval-benchmarking-the-hallucination-of","slug":"uhgeval-benchmarking-the-hallucination-of","title":"UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation","date":"2023-11-26","arxiv_id":"2311.15296","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["IAAR-Shanghai/UHGEval"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"cmed-gpt-prompt-tuning-for-entity-aware","title":"CMed-GPT: Prompt Tuning for Entity-Aware Chinese Medical Dialogue Generation","date":"2023-11-24","arxiv_id":"2311.14539","n_code_links":0,"syntology":null},{"paper":"/paper/data-to-text-bilingual-generation","slug":"data-to-text-bilingual-generation","title":"Data-to-Text Bilingual Generation","date":"2023-11-24","arxiv_id":"2311.14808","n_code_links":2,"syntology":null},{"paper":"/paper/gpt-struct-me-probing-gpt-models-on-narrative","slug":"gpt-struct-me-probing-gpt-models-on-narrative","title":"GPT Struct Me: Probing GPT Models on Narrative Entity Extraction","date":"2023-11-24","arxiv_id":"2311.14583","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-auditing-large-language-models","title":"Towards Auditing Large Language Models: Improving Text-based Stereotype Detection","date":"2023-11-23","arxiv_id":"2311.14126","n_code_links":0,"syntology":null},{"paper":"/paper/comparison-of-pipeline-sequence-to-sequence","slug":"comparison-of-pipeline-sequence-to-sequence","title":"Comparison of pipeline, sequence-to-sequence, and GPT models for end-to-end relation extraction: experiments with the rare disease use-case","date":"2023-11-22","arxiv_id":"2311.13729","n_code_links":1,"syntology":null},{"paper":null,"slug":"drilling-down-into-the-discourse-structure","title":"Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering","date":"2023-11-22","arxiv_id":"2311.13565","n_code_links":0,"syntology":null},{"paper":null,"slug":"academicgpt-empowering-academic-research","title":"AcademicGPT: Empowering Academic Research","date":"2023-11-21","arxiv_id":"2311.12315","n_code_links":0,"syntology":null},{"paper":"/paper/alpha-anomalous-physiological-health","slug":"alpha-anomalous-physiological-health","title":"ALPHA: AnomaLous Physiological Health Assessment Using Large Language Models","date":"2023-11-21","arxiv_id":"2311.12524","n_code_links":1,"syntology":null},{"paper":"/paper/descriptor-and-word-soups-overcoming-the","slug":"descriptor-and-word-soups-overcoming-the","title":"Descriptor and Word Soups: Overcoming the Parameter Efficiency Accuracy Tradeoff for Out-of-Distribution Few-shot Learning","date":"2023-11-21","arxiv_id":"2311.13612","n_code_links":1,"syntology":null},{"paper":"/paper/extracting-definienda-in-mathematical","slug":"extracting-definienda-in-mathematical","title":"Extracting Definienda in Mathematical Scholarly Articles with Transformers","date":"2023-11-21","arxiv_id":"2311.12448","n_code_links":2,"syntology":null},{"paper":null,"slug":"gpt4motion-scripting-physical-motions-in-text","title":"GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning","date":"2023-11-21","arxiv_id":"2311.12631","n_code_links":0,"syntology":null},{"paper":"/paper/assessing-prompt-injection-risks-in-200","slug":"assessing-prompt-injection-risks-in-200","title":"Assessing Prompt Injection Risks in 200+ Custom GPTs","date":"2023-11-20","arxiv_id":"2311.11538","n_code_links":1,"syntology":null},{"paper":"/paper/how-to-use-large-language-models-for-text","slug":"how-to-use-large-language-models-for-text","title":"Towards Human-Level Text Coding with LLMs: The Case of Fatherhood Roles in Public Policy Documents","date":"2023-11-20","arxiv_id":"2311.11844","n_code_links":1,"syntology":null},{"paper":null,"slug":"memorycompanion-a-smart-healthcare-solution","title":"MemoryCompanion: A Smart Healthcare Solution to Empower Efficient Alzheimer's Care Via Unleashing Generative AI","date":"2023-11-20","arxiv_id":"2311.14730","n_code_links":0,"syntology":null},{"paper":null,"slug":"bias-a-head-analyzing-bias-in-transformer","title":"Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads","date":"2023-11-17","arxiv_id":"2311.10395","n_code_links":0,"syntology":null},{"paper":"/paper/dynapipe-optimizing-multi-task-training","slug":"dynapipe-optimizing-multi-task-training","title":"DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines","date":"2023-11-17","arxiv_id":"2311.10418","n_code_links":2,"syntology":null},{"paper":"/paper/event-causality-is-key-to-computational-story","slug":"event-causality-is-key-to-computational-story","title":"Event Causality Is Key to Computational Story Understanding","date":"2023-11-16","arxiv_id":"2311.09648","n_code_links":1,"syntology":{"ran":6,"of":9,"n_ran_checked":6,"n_instrument":0,"unverified":3,"pointer_only":9,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["insundaycathy/event-causality-extraction"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"predictive-minds-llms-as-atypical-active","title":"Predictive Minds: LLMs As Atypical Active Inference Agents","date":"2023-11-16","arxiv_id":"2311.10215","n_code_links":0,"syntology":null},{"paper":null,"slug":"loke-linked-open-knowledge-extraction-for","title":"LOKE: Linked Open Knowledge Extraction for Automated Knowledge Graph Construction","date":"2023-11-15","arxiv_id":"2311.09366","n_code_links":0,"syntology":null},{"paper":"/paper/a-survey-on-language-models-for-code","slug":"a-survey-on-language-models-for-code","title":"Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code","date":"2023-11-14","arxiv_id":"2311.07989","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluating-llms-on-document-based-qa-exact","title":"Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset","date":"2023-11-14","arxiv_id":"2311.07878","n_code_links":0,"syntology":null},{"paper":"/paper/fair-abstractive-summarization-of-diverse","slug":"fair-abstractive-summarization-of-diverse","title":"Fair Abstractive Summarization of Diverse Perspectives","date":"2023-11-14","arxiv_id":"2311.07884","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-language-model-driven-classroom","title":"Large Language Model-Driven Classroom Flipping: Empowering Student-Centric Peer Questioning with Flipped Interaction","date":"2023-11-14","arxiv_id":"2311.14708","n_code_links":0,"syntology":null},{"paper":"/paper/in-context-learning-generalizes-but-not","slug":"in-context-learning-generalizes-but-not","title":"In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax","date":"2023-11-13","arxiv_id":"2311.07811","n_code_links":1,"syntology":null},{"paper":null,"slug":"establishing-performance-baselines-in-fine","title":"Establishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users","date":"2023-11-10","arxiv_id":"2311.05903","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-fine-tuning-chatgpt-for-news","title":"Exploring Fine-tuning ChatGPT for News Recommendation","date":"2023-11-10","arxiv_id":"2311.05850","n_code_links":0,"syntology":null},{"paper":"/paper/smart-agent-based-modeling-on-the-use-of","slug":"smart-agent-based-modeling-on-the-use-of","title":"Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations","date":"2023-11-10","arxiv_id":"2311.06330","n_code_links":4,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["roihn/sabm"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"geoformer-predicting-human-mobility-using","title":"GeoFormer: Predicting Human Mobility using Generative Pre-trained Transformer (GPT)","date":"2023-11-09","arxiv_id":"2311.05092","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-artificial-intelligence-technology","title":"Leveraging Artificial Intelligence Technology for Mapping Research to Sustainable Development Goals: A Case Study","date":"2023-11-09","arxiv_id":"2311.16162","n_code_links":0,"syntology":null},{"paper":"/paper/lumos-learning-agents-with-unified-data","slug":"lumos-learning-agents-with-unified-data","title":"Agent Lumos: Unified and Modular Training for Open-Source Language Agents","date":"2023-11-09","arxiv_id":"2311.05657","n_code_links":2,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["allenai/lumos"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/massive-editing-for-large-language-models-via","slug":"massive-editing-for-large-language-models-via","title":"Massive Editing for Large Language Models via Meta Learning","date":"2023-11-08","arxiv_id":"2311.04661","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["chenmientan/malmen"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/neuro-gpt-developing-a-foundation-model-for","slug":"neuro-gpt-developing-a-foundation-model-for","title":"Neuro-GPT: Towards A Foundation Model for EEG","date":"2023-11-07","arxiv_id":"2311.03764","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":4,"n_instrument":0,"unverified":2,"pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["wenhui0206/neurogpt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"measuring-five-accountable-talk-moves-to","title":"Measuring Five Accountable Talk Moves to Improve Instruction at Scale","date":"2023-11-02","arxiv_id":"2311.10749","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-gpt-powerful-enough-to-analyze-the","title":"Is GPT Powerful Enough to Analyze the Emotions of Memes?","date":"2023-11-01","arxiv_id":"2311.00223","n_code_links":0,"syntology":null},{"paper":null,"slug":"theory-of-mind-in-large-language-models","title":"Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests","date":"2023-10-31","arxiv_id":"2310.20320","n_code_links":0,"syntology":null},{"paper":null,"slug":"herd-using-multiple-smaller-llms-to-match-the","title":"Herd: Using multiple, smaller LLMs to match the performances of proprietary, large LLMs via an intelligent composer","date":"2023-10-30","arxiv_id":"2310.19902","n_code_links":0,"syntology":null},{"paper":"/paper/litcab-lightweight-calibration-of-language","slug":"litcab-lightweight-calibration-of-language","title":"LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses","date":"2023-10-30","arxiv_id":"2310.19208","n_code_links":1,"syntology":null},{"paper":"/paper/synthetic-imitation-edit-feedback-for-factual","slug":"synthetic-imitation-edit-feedback-for-factual","title":"Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization","date":"2023-10-30","arxiv_id":"2310.20033","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":7,"n_instrument":0,"unverified":2,"pointer_only":9,"phrase":"7 ran (of which 3 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["seasonyao/learnfromhumanedit"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":3,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"from-chatbots-to-phishbots-preventing","title":"From Chatbots to PhishBots? -- Preventing Phishing scams created using ChatGPT, Google Bard and Claude","date":"2023-10-29","arxiv_id":"2310.19181","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-synergy-of-speculative-decoding-and","title":"The Synergy of Speculative Decoding and Batching in Serving Large Language Models","date":"2023-10-28","arxiv_id":"2310.18813","n_code_links":0,"syntology":null},{"paper":"/paper/lost-in-translation-found-in-spans","slug":"lost-in-translation-found-in-spans","title":"Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media","date":"2023-10-27","arxiv_id":"2310.18205","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-llms-grade-short-answer-reading","title":"Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset","date":"2023-10-26","arxiv_id":"2310.18373","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-transcripts-to-insights-uncovering","title":"From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI","date":"2023-10-26","arxiv_id":"2310.17721","n_code_links":0,"syntology":null},{"paper":"/paper/lightlm-a-lightweight-deep-and-narrow","slug":"lightlm-a-lightweight-deep-and-narrow","title":"LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation","date":"2023-10-26","arxiv_id":"2310.17488","n_code_links":1,"syntology":{"ran":11,"of":12,"n_ran_checked":11,"n_instrument":0,"unverified":1,"pointer_only":12,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 1 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["dongyuanjushi/lightlm"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"mo-yolo-end-to-end-multiple-object-tracking","title":"DecoderTracker: Decoder-Only Method for Multiple-Object Tracking","date":"2023-10-26","arxiv_id":"2310.17170","n_code_links":0,"syntology":null},{"paper":"/paper/sliceformer-make-multi-head-attention-as","slug":"sliceformer-make-multi-head-attention-as","title":"Sliceformer: Make Multi-head Attention as Simple as Sorting in Discriminative Tasks","date":"2023-10-26","arxiv_id":"2310.17683","n_code_links":1,"syntology":null},{"paper":null,"slug":"zeroquant-hero-hardware-enhanced-robust","title":"ZeroQuant-HERO: Hardware-Enhanced Robust Optimized Post-Training Quantization Framework for W8A8 Transformers","date":"2023-10-26","arxiv_id":"2310.17723","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-gpt-models-follow-human-summarization","title":"Can GPT models Follow Human Summarization Guidelines? Evaluating ChatGPT and GPT-4 for Dialogue Summarization","date":"2023-10-25","arxiv_id":"2310.16810","n_code_links":0,"syntology":null},{"paper":null,"slug":"rcagent-cloud-root-cause-analysis-by","title":"RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models","date":"2023-10-25","arxiv_id":"2310.16340","n_code_links":0,"syntology":null},{"paper":null,"slug":"generative-pre-trained-transformer-for-1","title":"Generative Pre-trained Transformer for Vietnamese Community-based COVID-19 Question Answering","date":"2023-10-23","arxiv_id":"2310.14602","n_code_links":0,"syntology":null},{"paper":"/paper/the-continued-usefulness-of-vocabulary-tests","slug":"the-continued-usefulness-of-vocabulary-tests","title":"Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models","date":"2023-10-23","arxiv_id":"2310.14703","n_code_links":1,"syntology":null},{"paper":"/paper/is-chatgpt-a-game-changer-for-geocoding-a","slug":"is-chatgpt-a-game-changer-for-geocoding-a","title":"Is ChatGPT a game changer for geocoding -- a benchmark for geocoding address parsing techniques","date":"2023-10-22","arxiv_id":"2310.14360","n_code_links":1,"syntology":null},{"paper":"/paper/gemba-mqm-detecting-translation-quality-error","slug":"gemba-mqm-detecting-translation-quality-error","title":"GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4","date":"2023-10-21","arxiv_id":"2310.13988","n_code_links":1,"syntology":{"ran":8,"of":8,"n_ran_checked":8,"n_instrument":0,"unverified":0,"pointer_only":8,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"alltogether-investigating-the-efficacy-of","title":"AllTogether: Investigating the Efficacy of Spliced Prompt for Web Navigation using Large Language Models","date":"2023-10-20","arxiv_id":"2310.18331","n_code_links":0,"syntology":null},{"paper":null,"slug":"challenges-and-contributing-factors-in-the","title":"Challenges and Contributing Factors in the Utilization of Large Language Models (LLMs)","date":"2023-10-20","arxiv_id":"2310.13343","n_code_links":0,"syntology":null},{"paper":null,"slug":"equivariant-transformer-is-all-you-need","title":"Equivariant Transformer is all you need","date":"2023-10-20","arxiv_id":"2310.13222","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-training-for-conversational-question","title":"Robust Training for Conversational Question Answering Models with Reinforced Reformulation Generation","date":"2023-10-20","arxiv_id":"2310.13505","n_code_links":0,"syntology":null},{"paper":null,"slug":"laser-linear-compression-in-wireless","title":"LASER: Linear Compression in Wireless Distributed Optimization","date":"2023-10-19","arxiv_id":"2310.13033","n_code_links":0,"syntology":null},{"paper":null,"slug":"not-all-countries-celebrate-thanksgiving-on","title":"Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models","date":"2023-10-19","arxiv_id":"2310.12481","n_code_links":0,"syntology":null},{"paper":"/paper/the-shifted-and-the-overlooked-a-task","slug":"the-shifted-and-the-overlooked-a-task","title":"The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions","date":"2023-10-19","arxiv_id":"2310.12418","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ozyyshr/sharegpt_investigation"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"solving-the-multiplication-problem-of-a-large","title":"Solving the multiplication problem of a large language model system using a graph-based method","date":"2023-10-18","arxiv_id":"2310.13016","n_code_links":0,"syntology":null},{"paper":null,"slug":"emergent-ai-assisted-discourse-case-study-of","title":"Emergent AI-Assisted Discourse: Case Study of a Second Language Writer Authoring with ChatGPT","date":"2023-10-17","arxiv_id":"2310.10903","n_code_links":0,"syntology":null},{"paper":"/paper/data-contamination-through-the-lens-of-time","slug":"data-contamination-through-the-lens-of-time","title":"Data Contamination Through the Lens of Time","date":"2023-10-16","arxiv_id":"2310.10628","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["abacusai/to-the-cutoff"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"moconvq-unified-physics-based-motion-control","title":"MoConVQ: Unified Physics-Based Motion Control via Scalable Discrete Representations","date":"2023-10-16","arxiv_id":"2310.10198","n_code_links":0,"syntology":null}],"record_sha256":"e8129cc6112c1481005c4391582c869683658ca8e3eb54cb3ee652d868bcf5ac","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}