{"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":"/task/prompt-engineering/papers/7","list_of":"/task/prompt-engineering","task":"Prompt Engineering","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":7,"pages_in_order":13,"rows_per_page":100,"rows":[601,700],"of":1236,"counts":{"archive_papers_tagged":1236,"with_a_code_link":454,"where_syntology_ran_a_sample":143,"not_listed_spam_title":0,"listed":1236,"listed_where_code_ran":143,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":118,"every_run_a_failure_of_syntologys_instrument":25,"listed_with_a_run_with_no_instrument_failure":118,"listed_every_run_a_failure_of_syntologys_instrument":25,"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":"/task/prompt-engineering","prev":"/task/prompt-engineering/papers/6","next":"/task/prompt-engineering/papers/8","papers":[{"url":null,"slug":"bokeh-diffusion-defocus-blur-control-in-text","title":"Bokeh Diffusion: Defocus Blur Control in Text-to-Image Diffusion Models","date":"2025-03-11","arxiv_id":"2503.08434","repositories_listed":0,"syntology":null},{"url":null,"slug":"instruction-augmented-long-horizon-planning","title":"Instruction-Augmented Long-Horizon Planning: Embedding Grounding Mechanisms in Embodied Mobile Manipulation","date":"2025-03-11","arxiv_id":"2503.08084","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-chinese-medical-llms-a-medbench","title":"Benchmarking Chinese Medical LLMs: A Medbench-based Analysis of Performance Gaps and Hierarchical Optimization Strategies","date":"2025-03-10","arxiv_id":"2503.07306","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-the-automated-labeling-method","title":"Evaluation of the Automated Labeling Method for Taxonomic Nomenclature Through Prompt-Optimized Large Language Model","date":"2025-03-08","arxiv_id":"2503.10662","repositories_listed":0,"syntology":null},{"url":null,"slug":"generation-of-optimized-solidity-code-for","title":"Generation of Optimized Solidity Code for Machine Learning Models using LLMs","date":"2025-03-08","arxiv_id":"2503.06203","repositories_listed":0,"syntology":null},{"url":null,"slug":"cognitive-bias-detection-using-advanced","title":"Cognitive Bias Detection Using Advanced Prompt Engineering","date":"2025-03-07","arxiv_id":"2503.05516","repositories_listed":0,"syntology":null},{"url":null,"slug":"jailbreaking-is-mostly-simpler-than-you-think","title":"Jailbreaking is (Mostly) Simpler Than You Think","date":"2025-03-07","arxiv_id":"2503.05264","repositories_listed":0,"syntology":null},{"url":null,"slug":"interchat-enhancing-generative-visual","title":"InterChat: Enhancing Generative Visual Analytics using Multimodal Interactions","date":"2025-03-06","arxiv_id":"2503.04110","repositories_listed":0,"syntology":null},{"url":null,"slug":"toolfuzz-automated-agent-tool-testing","title":"ToolFuzz -- Automated Agent Tool Testing","date":"2025-03-06","arxiv_id":"2503.04479","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-evolved-preference-optimization-for","title":"Self-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models","date":"2025-03-04","arxiv_id":"2503.04813","repositories_listed":0,"syntology":null},{"url":null,"slug":"text2scenario-text-driven-scenario-generation","title":"Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test","date":"2025-03-04","arxiv_id":"2503.02911","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-agnostic-automated-assessment-of","title":"Language-agnostic, automated assessment of listeners' speech recall using large language models","date":"2025-03-02","arxiv_id":"2503.01045","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-prompt-optimization-via-heuristic","title":"Automatic Prompt Optimization via Heuristic Search: A Survey","date":"2025-02-26","arxiv_id":"2502.18746","repositories_listed":0,"syntology":null},{"url":null,"slug":"static-vs-agentic-game-master-ai-for","title":"Static Vs. Agentic Game Master AI for Facilitating Solo Role-Playing Experiences","date":"2025-02-26","arxiv_id":"2502.19519","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-large-language-models-extract-customer","title":"Can Large Language Models Extract Customer Needs as well as Professional Analysts?","date":"2025-02-25","arxiv_id":"2503.01870","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-survey-of-automatic-prompt","title":"A Systematic Survey of Automatic Prompt Optimization Techniques","date":"2025-02-24","arxiv_id":"2502.16923","repositories_listed":0,"syntology":null},{"url":null,"slug":"representation-engineering-for-large-language","title":"Representation Engineering for Large-Language Models: Survey and Research Challenges","date":"2025-02-24","arxiv_id":"2502.17601","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-large-vision-language-models-detect","title":"Can Large Vision-Language Models Detect Images Copyright Infringement from GenAI?","date":"2025-02-23","arxiv_id":"2502.16618","repositories_listed":0,"syntology":null},{"url":null,"slug":"navigation-gpt-a-robust-and-adaptive","title":"Navigation-GPT: A Robust and Adaptive Framework Utilizing Large Language Models for Navigation Applications","date":"2025-02-23","arxiv_id":"2502.16402","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-query-product-relevance-labeling","title":"Automated Query-Product Relevance Labeling using Large Language Models for E-commerce Search","date":"2025-02-21","arxiv_id":"2502.15990","repositories_listed":0,"syntology":null},{"url":null,"slug":"automedprompt-a-new-framework-for-optimizing","title":"AutoMedPrompt: A New Framework for Optimizing LLM Medical Prompts Using Textual Gradients","date":"2025-02-21","arxiv_id":"2502.15944","repositories_listed":0,"syntology":null},{"url":null,"slug":"chats-grid-an-iterative-retrieval-q-a","title":"Chats-Grid: An Iterative Retrieval Q&A Optimization Scheme Leveraging Large Model and Retrieval Enhancement Generation in smart grid","date":"2025-02-21","arxiv_id":"2502.15583","repositories_listed":0,"syntology":null},{"url":null,"slug":"effects-of-prompt-length-on-domain-specific","title":"Effects of Prompt Length on Domain-specific Tasks for Large Language Models","date":"2025-02-20","arxiv_id":"2502.14255","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-knowledge-generation-to-knowledge","title":"From Knowledge Generation to Knowledge Verification: Examining the BioMedical Generative Capabilities of ChatGPT","date":"2025-02-20","arxiv_id":"2502.14714","repositories_listed":0,"syntology":null},{"url":null,"slug":"quad-llm-mltc-large-language-models-ensemble","title":"QUAD-LLM-MLTC: Large Language Models Ensemble Learning for Healthcare Text Multi-Label Classification","date":"2025-02-20","arxiv_id":"2502.14189","repositories_listed":0,"syntology":null},{"url":null,"slug":"navigating-semantic-relations-challenges-for","title":"Navigating Semantic Relations: Challenges for Language Models in Abstract Common-Sense Reasoning","date":"2025-02-19","arxiv_id":"2502.14086","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-education-with-generative-ai-and","title":"Personalized Education with Generative AI and Digital Twins: VR, RAG, and Zero-Shot Sentiment Analysis for Industry 4.0 Workforce Development","date":"2025-02-19","arxiv_id":"2502.14080","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompting-a-weighting-mechanism-into-llm-as-a","title":"Prompting a Weighting Mechanism into LLM-as-a-Judge in Two-Step: A Case Study","date":"2025-02-19","arxiv_id":"2502.13396","repositories_listed":0,"syntology":null},{"url":null,"slug":"rag-gym-optimizing-reasoning-and-search","title":"RAG-Gym: Optimizing Reasoning and Search Agents with Process Supervision","date":"2025-02-19","arxiv_id":"2502.13957","repositories_listed":0,"syntology":null},{"url":null,"slug":"um-fhs-at-trec-2024-plaba-exploration-of-fine","title":"UM_FHS at TREC 2024 PLABA: Exploration of Fine-tuning and AI agent approach for plain language adaptations of biomedical text","date":"2025-02-19","arxiv_id":"2502.14144","repositories_listed":0,"syntology":null},{"url":null,"slug":"edge-efficient-data-selection-for-llm-agents","title":"EDGE: Efficient Data Selection for LLM Agents via Guideline Effectiveness","date":"2025-02-18","arxiv_id":"2502.12494","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-automatic-prompt-engineering-an","title":"A Survey of Automatic Prompt Engineering: An Optimization Perspective","date":"2025-02-17","arxiv_id":"2502.11560","repositories_listed":0,"syntology":null},{"url":null,"slug":"ado-automatic-data-optimization-for-inputs-in","title":"ADO: Automatic Data Optimization for Inputs in LLM Prompts","date":"2025-02-17","arxiv_id":"2502.11436","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-large-language-models-in-healthcare","title":"Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics","date":"2025-02-17","arxiv_id":"2502.11861","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligent-mobile-ai-generated-content","title":"Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning","date":"2025-02-17","arxiv_id":"2502.11386","repositories_listed":0,"syntology":null},{"url":null,"slug":"unitcoder-scalable-iterative-code-synthesis","title":"UnitCoder: Scalable Iterative Code Synthesis with Unit Test Guidance","date":"2025-02-17","arxiv_id":"2502.11460","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompting-in-the-dark-assessing-human","title":"Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent","date":"2025-02-16","arxiv_id":"2502.11267","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcgrllm-large-language-model-driven-reward","title":"PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning","date":"2025-02-15","arxiv_id":"2502.10906","repositories_listed":0,"syntology":null},{"url":null,"slug":"has-my-system-prompt-been-used-large-language","title":"Has My System Prompt Been Used? Large Language Model Prompt Membership Inference","date":"2025-02-14","arxiv_id":"2502.09974","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-gpt-for-video-understanding-zero","title":"Optimizing GPT for Video Understanding: Zero-Shot Performance and Prompt Engineering","date":"2025-02-13","arxiv_id":"2502.09573","repositories_listed":0,"syntology":null},{"url":null,"slug":"evoflow-evolving-diverse-agentic-workflows-on","title":"EvoFlow: Evolving Diverse Agentic Workflows On The Fly","date":"2025-02-11","arxiv_id":"2502.07373","repositories_listed":0,"syntology":null},{"url":null,"slug":"proceedings-40th-international-conference-on","title":"Proceedings 40th International Conference on Logic Programming","date":"2025-02-11","arxiv_id":"2502.08453","repositories_listed":0,"syntology":null},{"url":null,"slug":"snipgen-a-mining-repository-framework-for","title":"SnipGen: A Mining Repository Framework for Evaluating LLMs for Code","date":"2025-02-10","arxiv_id":"2502.07046","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-prompt-engineering-techniques","title":"Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models","date":"2025-02-09","arxiv_id":"2502.06039","repositories_listed":0,"syntology":null},{"url":null,"slug":"maga-massive-genre-audience-reformulation-to","title":"Reformulation for Pretraining Data Augmentation","date":"2025-02-06","arxiv_id":"2502.04235","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-prompt-optimization-techniques","title":"Automatic Prompt Optimization Techniques: Exploring the Potential for Synthetic Data Generation","date":"2025-02-05","arxiv_id":"2502.03078","repositories_listed":0,"syntology":null},{"url":null,"slug":"facter-fairness-aware-conformal-thresholding","title":"FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems","date":"2025-02-05","arxiv_id":"2502.02966","repositories_listed":0,"syntology":null},{"url":null,"slug":"kda-a-knowledge-distilled-attacker-for","title":"KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs","date":"2025-02-05","arxiv_id":"2502.05223","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-are-universal","title":"Large Language Model as Universal Retriever in Industrial-Scale Recommender System","date":"2025-02-05","arxiv_id":"2502.03041","repositories_listed":0,"syntology":null},{"url":null,"slug":"optic-optimizing-patient-provider-triaging","title":"OPTIC: Optimizing Patient-Provider Triaging & Improving Communications in Clinical Operations using GPT-4 Data Labeling and Model Distillation","date":"2025-02-05","arxiv_id":"2503.05701","repositories_listed":0,"syntology":null},{"url":null,"slug":"arbitrary-data-as-images-fusion-of-patient","title":"Arbitrary Data as Images: Fusion of Patient Data Across Modalities and Irregular Intervals with Vision Transformers","date":"2025-01-30","arxiv_id":"2501.18237","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-re-id-meets-lvlms-what-can-we-expect","title":"Human Re-ID Meets LVLMs: What can we expect?","date":"2025-01-30","arxiv_id":"2501.18698","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-optimization-of-prompt-security-and","title":"Joint Optimization of Prompt Security and System Performance in Edge-Cloud LLM Systems","date":"2025-01-30","arxiv_id":"2501.18663","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-llm-agents-for-automated","title":"Leveraging LLM Agents for Automated Optimization Modeling for SASP Problems: A Graph-RAG based Approach","date":"2025-01-30","arxiv_id":"2501.18320","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-web-and-creative-ai-a-technical","title":"Semantic Web and Creative AI -- A Technical Report from ISWS 2023","date":"2025-01-30","arxiv_id":"2501.18542","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-optimized-framework-for","title":"Few-Shot Optimized Framework for Hallucination Detection in Resource-Limited NLP Systems","date":"2025-01-28","arxiv_id":"2501.16616","repositories_listed":0,"syntology":null},{"url":null,"slug":"implementation-of-a-generative-ai-assistant","title":"Implementation of a Generative AI Assistant in K-12 Education: The CyberScholar Initiative","date":"2025-01-28","arxiv_id":"2502.19422","repositories_listed":0,"syntology":null},{"url":null,"slug":"irony-detection-reasoning-and-understanding","title":"Irony Detection, Reasoning and Understanding in Zero-shot Learning","date":"2025-01-28","arxiv_id":"2501.16884","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-source-retrieval-augmented-generation","title":"Open-Source Retrieval Augmented Generation Framework for Retrieving Accurate Medication Insights from Formularies for African Healthcare Workers","date":"2025-01-28","arxiv_id":"2502.15722","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphicl-unlocking-graph-learning-potential","title":"GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design","date":"2025-01-27","arxiv_id":"2501.15755","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-well-can-llms-grade-essays-in-arabic","title":"How well can LLMs Grade Essays in Arabic?","date":"2025-01-27","arxiv_id":"2501.16516","repositories_listed":0,"syntology":null},{"url":null,"slug":"auto-prompting-sam-for-weakly-supervised","title":"Auto-Prompting SAM for Weakly Supervised Landslide Extraction","date":"2025-01-23","arxiv_id":"2501.13426","repositories_listed":0,"syntology":null},{"url":"/paper/dual-modal-prototype-joint-learning-for","slug":"dual-modal-prototype-joint-learning-for","title":"Dual-Modal Prototype Joint Learning for Compositional Zero-Shot Learning","date":"2025-01-23","arxiv_id":"2501.13859","repositories_listed":0,"syntology":{"n":8,"n_ran":4,"n_constructed":3,"n_ran_checked":4,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":8,"phrase":"4 ran (of which 3 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) · 4 unverified","sample_list":"/paper/dual-modal-prototype-joint-learning-for#ran","syntology_url":"https://syntology.ai/paper/2501.13859","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2501.13859"}},"official":null}},{"url":null,"slug":"precisecam-precise-camera-control-for-text-to","title":"PreciseCam: Precise Camera Control for Text-to-Image Generation","date":"2025-01-22","arxiv_id":"2501.12910","repositories_listed":0,"syntology":null},{"url":null,"slug":"conversation-routines-a-prompt-engineering","title":"Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems","date":"2025-01-20","arxiv_id":"2501.11613","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-ml-based-detection-and-categorization-of","title":"AI/ML Based Detection and Categorization of Covert Communication in IPv6 Network","date":"2025-01-18","arxiv_id":"2501.10627","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-generalization-in-chain-of-thought","title":"Enhancing Generalization in Chain of Thought Reasoning for Smaller Models","date":"2025-01-16","arxiv_id":"2501.09804","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangling-exploration-of-large-language","title":"Disentangling Exploration of Large Language Models by Optimal Exploitation","date":"2025-01-15","arxiv_id":"2501.08925","repositories_listed":0,"syntology":null},{"url":null,"slug":"duplex-dual-prototype-learning-for","title":"Duplex: Dual Prototype Learning for Compositional Zero-Shot Learning","date":"2025-01-13","arxiv_id":"2501.07114","repositories_listed":0,"syntology":null},{"url":null,"slug":"initial-findings-on-sensor-based-open","title":"Initial Findings on Sensor based Open Vocabulary Activity Recognition via Text Embedding Inversion","date":"2025-01-13","arxiv_id":"2501.07408","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-evaluation-of-large-language-5","title":"A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context","date":"2025-01-12","arxiv_id":"2501.06859","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaffolding-creativity-integrating-generative","title":"Scaffolding Creativity: Integrating Generative AI Tools and Real-world Experiences in Business Education","date":"2025-01-11","arxiv_id":"2501.06527","repositories_listed":0,"syntology":null},{"url":null,"slug":"callnavi-a-study-and-challenge-on-function","title":"CallNavi, A Challenge and Empirical Study on LLM Function Calling and Routing","date":"2025-01-09","arxiv_id":"2501.05255","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-to-text-prompt-engineering-in","title":"Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization","date":"2025-01-09","arxiv_id":"2501.05079","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-large-language-models-for-semantic","title":"Exploring Large Language Models for Semantic Analysis and Categorization of Android Malware","date":"2025-01-08","arxiv_id":"2501.04848","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-sequential-optimal-learning-approach-to","title":"A Sequential Optimal Learning Approach to Automated Prompt Engineering in Large Language Models","date":"2025-01-07","arxiv_id":"2501.03508","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-code-to-compliance-assessing-chatgpt-s","title":"From Code to Compliance: Assessing ChatGPT's Utility in Designing an Accessible Webpage -- A Case Study","date":"2025-01-07","arxiv_id":"2501.03572","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-chatgpt-implement-finite-element-models","title":"Can ChatGPT implement finite element models for geotechnical engineering applications?","date":"2025-01-04","arxiv_id":"2501.02199","repositories_listed":0,"syntology":null},{"url":null,"slug":"recursive-decomposition-of-logical-thoughts","title":"Recursive Decomposition of Logical Thoughts: Framework for Superior Reasoning and Knowledge Propagation in Large Language Models","date":"2025-01-03","arxiv_id":"2501.02026","repositories_listed":0,"syntology":null},{"url":null,"slug":"harnessing-multi-agent-llms-for-complex","title":"Harnessing Multi-Agent LLMs for Complex Engineering Problem-Solving: A Framework for Senior Design Projects","date":"2025-01-02","arxiv_id":"2501.01205","repositories_listed":0,"syntology":null},{"url":null,"slug":"gpt-4-on-clinic-depression-assessment-an-llm","title":"GPT-4 on Clinic Depression Assessment: An LLM-Based Pilot Study","date":"2024-12-31","arxiv_id":"2501.00199","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-synergy-of-automated-pipelines-with","title":"The Synergy of Automated Pipelines with Prompt Engineering and Generative AI in Web Crawling","date":"2024-12-29","arxiv_id":"2502.15691","repositories_listed":0,"syntology":null},{"url":null,"slug":"extract-information-from-hybrid-long","title":"Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset","date":"2024-12-28","arxiv_id":"2412.20072","repositories_listed":0,"syntology":null},{"url":null,"slug":"renaissance-of-literate-programming-in-the","title":"Renaissance of Literate Programming in the Era of LLMs: Enhancing LLM-Based Code Generation in Large-Scale Projects","date":"2024-12-25","arxiv_id":"2502.17441","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrato360-2-0-a-document-and-database","title":"Contrato360 2.0: A Document and Database-Driven Question-Answer System using Large Language Models and Agents","date":"2024-12-23","arxiv_id":"2412.17942","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-multi-agent-orchestration-and","title":"Dynamic Multi-Agent Orchestration and Retrieval for Multi-Source Question-Answer Systems using Large Language Models","date":"2024-12-23","arxiv_id":"2412.17964","repositories_listed":0,"syntology":null},{"url":null,"slug":"erupd-english-to-roman-urdu-parallel-dataset","title":"ERUPD -- English to Roman Urdu Parallel Dataset","date":"2024-12-23","arxiv_id":"2412.17562","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-fusing-chatgpt-and-ensemble-learning-in","title":"On Fusing ChatGPT and Ensemble Learning in Discon-tinuous Named Entity Recognition in Health Corpora","date":"2024-12-22","arxiv_id":"2412.16976","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-guided-knowledgeable-network-of-thoughts","title":"Self-guided Knowledgeable Network of Thoughts: Amplifying Reasoning with Large Language Models","date":"2024-12-21","arxiv_id":"2412.16533","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-machine-learning-approach-for-emergency","title":"A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models","date":"2024-12-20","arxiv_id":"2412.16341","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-framework-for-critical-evaluation-of-text","title":"A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering","date":"2024-12-17","arxiv_id":"2412.12774","repositories_listed":0,"syntology":null},{"url":null,"slug":"iprop-interactive-prompt-optimization-for","title":"iPrOp: Interactive Prompt Optimization for Large Language Models with a Human in the Loop","date":"2024-12-17","arxiv_id":"2412.12644","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-is-knowledge-graph-reasoner-llm-s","title":"LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential Recommendation","date":"2024-12-17","arxiv_id":"2412.12464","repositories_listed":0,"syntology":null},{"url":null,"slug":"samic-segment-anything-with-in-context","title":"SAMIC: Segment Anything with In-Context Spatial Prompt Engineering","date":"2024-12-16","arxiv_id":"2412.11998","repositories_listed":0,"syntology":null},{"url":null,"slug":"token-prepending-a-training-free-approach-for","title":"Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs","date":"2024-12-16","arxiv_id":"2412.11556","repositories_listed":0,"syntology":null},{"url":null,"slug":"streamlining-systematic-reviews-a-novel","title":"Streamlining Systematic Reviews: A Novel Application of Large Language Models","date":"2024-12-14","arxiv_id":"2412.15247","repositories_listed":0,"syntology":null},{"url":null,"slug":"tacomore-leveraging-the-potential-of-llms-in","title":"TACOMORE: Leveraging the Potential of LLMs in Corpus-based Discourse Analysis with Prompt Engineering","date":"2024-12-13","arxiv_id":"2412.10139","repositories_listed":0,"syntology":null},{"url":null,"slug":"antelope-potent-and-concealed-jailbreak","title":"Antelope: Potent and Concealed Jailbreak Attack Strategy","date":"2024-12-11","arxiv_id":"2412.08156","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-graph-rag-and-prompt-engineering","title":"Leveraging Graph-RAG and Prompt Engineering to Enhance LLM-Based Automated Requirement Traceability and Compliance Checks","date":"2024-12-11","arxiv_id":"2412.08593","repositories_listed":0,"syntology":null},{"url":null,"slug":"magic-mastering-physical-adversarial","title":"MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents","date":"2024-12-11","arxiv_id":"2412.08014","repositories_listed":0,"syntology":null}],"record_sha256":"b52f86435f7cf35bcbe5318db30847329f8698b6a7a89a55a418ea416d2c5f4d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}