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| "title": "OPT: Open Pre-trained Transformer Language Models" |
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| "title": "Measuring Massive Multitask Language Understanding" |
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| "title": "Deep Reinforcement Learning from Human Preferences" |
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| "title": "A Survey of Large Language Models" |
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| "title": "Fine-Tuning Language Models from Human Preferences" |
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| "title": "A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity" |
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| "title": "Measuring Mathematical Problem Solving With the MATH Dataset" |
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| "title": "GLM-130B: An Open Bilingual Pre-trained Model" |
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| "title": "Adversarial NLI: A New Benchmark for Natural Language Understanding" |
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| "title": "CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis" |
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| "title": "Is ChatGPT a General-Purpose Natural Language Processing Task Solver?" |
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| "title": "Aligning AI With Shared Human Values" |
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| "title": "Large Language Models are not Fair Evaluators" |
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| "title": "Is ChatGPT a Good NLG Evaluator? A Preliminary Study" |
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| "title": "MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models" |
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| "title": "Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback" |
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| "title": "Towards a Unified Multi-Dimensional Evaluator for Text Generation" |
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| "title": "Recommender Systems in the Era of Large Language Models (LLMs)" |
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| "title": "Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models" |
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| "title": "Societal Biases in Language Generation: Progress and Challenges" |
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| "title": "Tool Learning with Foundation Models" |
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| "title": "Can Large Language Models Transform Computational Social Science?" |
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| "title": "The Unsurprising Effectiveness of Pre-Trained Vision Models for Control" |
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| "title": "CMMLU: Measuring massive multitask language understanding in Chinese" |
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| "title": "PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization" |
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| "title": "Sentiment Analysis in the Era of Large Language Models: A Reality Check" |
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| "title": "On the Planning Abilities of Large Language Models - A Critical Investigation" |
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| "title": "Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential" |
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| "arxivId": "2305.18486", |
| "title": "A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets" |
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| "title": "The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation" |
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| "title": "CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review" |
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| "title": "Uncovering ChatGPT\u2019s Capabilities in Recommender Systems" |
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| "title": "Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning" |
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| "title": "PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts" |
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| "title": "Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks" |
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| "title": "Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study" |
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| "arxivId": "2305.07609", |
| "title": "Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation" |
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| "title": "Autoformalization with Large Language Models" |
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| "arxivId": "2205.12255", |
| "title": "TALM: Tool Augmented Language Models" |
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| "arxivId": "2306.06687", |
| "title": "LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark" |
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| "arxivId": "2304.04339", |
| "title": "Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study" |
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| "title": "FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation" |
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| "title": "LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models" |
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| "arxivId": "2304.07619", |
| "title": "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models" |
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| "arxivId": "2303.13835", |
| "title": "Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited" |
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| "title": "MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning" |
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| "arxivId": "2309.10691", |
| "title": "MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback" |
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| "arxivId": "1804.02667", |
| "title": "J-PLUS: The Javalambre Photometric Local Universe Survey" |
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| "title": "How well do Large Language Models perform in Arithmetic tasks?" |
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| "arxivId": "2305.16934", |
| "title": "On Evaluating Adversarial Robustness of Large Vision-Language Models" |
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| "arxivId": "2309.11998", |
| "title": "LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset" |
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| "title": "Evaluating large language models on a highly-specialized topic, radiation oncology physics" |
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| "title": "Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance" |
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| "title": "Benchmarking Foundation Models with Language-Model-as-an-Examiner" |
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| "arxivId": "2307.00184", |
| "title": "Personality Traits in Large Language Models" |
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| "arxivId": "2304.02210", |
| "title": "Document-Level Machine Translation with Large Language Models" |
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| "arxivId": "2306.05715", |
| "title": "Exploring the Responses of Large Language Models to Beginner Programmers\u2019 Help Requests" |
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| "arxivId": "2305.13711", |
| "title": "LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models" |
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| "arxivId": "2304.07333", |
| "title": "The Self-Perception and Political Biases of ChatGPT" |
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| "arxivId": "2303.16421", |
| "title": "ChatGPT Is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models" |
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| "arxivId": "2308.01862", |
| "title": "Wider and Deeper LLM Networks are Fairer LLM Evaluators" |
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| "arxivId": "2211.08073", |
| "title": "GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective" |
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| "arxivId": "2305.12474", |
| "title": "Evaluating the Performance of Large Language Models on GAOKAO Benchmark" |
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| "arxivId": "2307.09705", |
| "title": "CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility" |
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| "arxivId": "2306.05179", |
| "title": "M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models" |
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| "arxivId": "2302.06706", |
| "title": "On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)" |
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| "arxivId": "2205.00445", |
| "title": "MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning" |
| }, |
| "2305.15269": { |
| "arxivId": "2305.15269", |
| "title": "Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples" |
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| "2305.11171": { |
| "arxivId": "2305.11171", |
| "title": "TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models" |
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| "2304.00723": { |
| "arxivId": "2304.00723", |
| "title": "Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: A Preliminary Empirical Study" |
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| "2106.06052": { |
| "arxivId": "2106.06052", |
| "title": "Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking" |
| }, |
| "2309.07045": { |
| "arxivId": "2309.07045", |
| "title": "SafetyBench: Evaluating the Safety of Large Language Models with Multiple Choice Questions" |
| }, |
| "2308.08833": { |
| "arxivId": "2308.08833", |
| "title": "CMB: A Comprehensive Medical Benchmark in Chinese" |
| }, |
| "2305.14938": { |
| "arxivId": "2305.14938", |
| "title": "Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark" |
| }, |
| "2306.07799": { |
| "arxivId": "2306.07799", |
| "title": "ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer" |
| }, |
| "2306.09296": { |
| "arxivId": "2306.09296", |
| "title": "KoLA: Carefully Benchmarking World Knowledge of Large Language Models" |
| }, |
| "2306.04757": { |
| "arxivId": "2306.04757", |
| "title": "InstructEval: Towards Holistic Evaluation of Instruction-Tuned Large Language Models" |
| }, |
| "2306.09841": { |
| "arxivId": "2306.09841", |
| "title": "Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation From Deductive, Inductive and Abductive Views" |
| }, |
| "2307.09042": { |
| "arxivId": "2307.09042", |
| "title": "Emotional intelligence of Large Language Models" |
| }, |
| "2306.01248": { |
| "arxivId": "2306.01248", |
| "title": "How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?" |
| }, |
| "2306.05783": { |
| "arxivId": "2306.05783", |
| "title": "Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation" |
| }, |
| "2306.03090": { |
| "arxivId": "2306.03090", |
| "title": "Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction" |
| }, |
| "2301.12868": { |
| "arxivId": "2301.12868", |
| "title": "On Robustness of Prompt-based Semantic Parsing with Large Pre-trained Language Model: An Empirical Study on Codex" |
| }, |
| "2209.12106": { |
| "arxivId": "2209.12106", |
| "title": "Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identity" |
| }, |
| "2306.04618": { |
| "arxivId": "2306.04618", |
| "title": "Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations" |
| }, |
| "2306.01337": { |
| "arxivId": "2306.01337", |
| "title": "MathChat: Converse to Tackle Challenging Math Problems with LLM Agents" |
| }, |
| "2306.07075": { |
| "arxivId": "2306.07075", |
| "title": "Large language models as tax attorneys: a case study in legal capabilities emergence" |
| }, |
| "2305.11700": { |
| "arxivId": "2305.11700", |
| "title": "Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights" |
| }, |
| "2305.18365": { |
| "arxivId": "2305.18365", |
| "title": "What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks" |
| }, |
| "2305.15074": { |
| "arxivId": "2305.15074", |
| "title": "Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language Models" |
| }, |
| "2303.02155": { |
| "arxivId": "2303.02155", |
| "title": "ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design" |
| }, |
| "2301.11596": { |
| "arxivId": "2301.11596", |
| "title": "ThoughtSource: A central hub for large language model reasoning data" |
| }, |
| "2306.11507": { |
| "arxivId": "2306.11507", |
| "title": "TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Models" |
| }, |
| "2305.16151": { |
| "arxivId": "2305.16151", |
| "title": "Understanding the Capabilities of Large Language Models for Automated Planning" |
| }, |
| "2308.03656": { |
| "arxivId": "2308.03656", |
| "title": "Emotionally Numb or Empathetic? Evaluating How LLMs Feel Using EmotionBench" |
| }, |
| "2306.01694": { |
| "arxivId": "2306.01694", |
| "title": "Evaluating Language Models for Mathematics through Interactions" |
| }, |
| "2309.09150": { |
| "arxivId": "2309.09150", |
| "title": "Can Large Language Models Understand Real-World Complex Instructions?" |
| }, |
| "2303.07142": { |
| "arxivId": "2303.07142", |
| "title": "Large Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification" |
| }, |
| "2205.09148": { |
| "arxivId": "2205.09148", |
| "title": "DDXPlus: A New Dataset For Automatic Medical Diagnosis" |
| }, |
| "2307.13692": { |
| "arxivId": "2307.13692", |
| "title": "ARB: Advanced Reasoning Benchmark for Large Language Models" |
| }, |
| "2305.16837": { |
| "arxivId": "2305.16837", |
| "title": "ChatGPT: A Study on its Utility for Ubiquitous Software Engineering Tasks" |
| }, |
| "2306.10512": { |
| "arxivId": "2306.10512", |
| "title": "From Static Benchmarks to Adaptive Testing: Psychometrics in AI Evaluation" |
| }, |
| "2301.12307": { |
| "arxivId": "2301.12307", |
| "title": "MQAG: Multiple-choice Question Answering and Generation for Assessing Information Consistency in Summarization" |
| }, |
| "2212.02774": { |
| "arxivId": "2212.02774", |
| "title": "Adaptive Testing of Computer Vision Models" |
| }, |
| "2306.02408": { |
| "arxivId": "2306.02408", |
| "title": "Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning" |
| }, |
| "2307.01135": { |
| "arxivId": "2307.01135", |
| "title": "ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience" |
| }, |
| "2304.00228": { |
| "arxivId": "2304.00228", |
| "title": "Accuracy and Political Bias of News Source Credibility Ratings by Large Language Models" |
| }, |
| "2306.16636": { |
| "arxivId": "2306.16636", |
| "title": "CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?" |
| }, |
| "2306.04504": { |
| "arxivId": "2306.04504", |
| "title": "Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformers" |
| }, |
| "2306.04308": { |
| "arxivId": "2306.04308", |
| "title": "Personality testing of GPT-3: Limited temporal reliability, but highlighted social desirability of GPT-3's personality instruments results" |
| }, |
| "2305.10263": { |
| "arxivId": "2305.10263", |
| "title": "M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models" |
| }, |
| "2305.01181": { |
| "arxivId": "2305.01181", |
| "title": "A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models" |
| }, |
| "2306.13651": { |
| "arxivId": "2306.13651", |
| "title": "Bring Your Own Data! Self-Supervised Evaluation for Large Language Models" |
| }, |
| "2306.06331": { |
| "arxivId": "2306.06331", |
| "title": "Investigating the Effectiveness of ChatGPT in Mathematical Reasoning and Problem Solving: Evidence from the Vietnamese National High School Graduation Examination" |
| }, |
| "2305.11792": { |
| "arxivId": "2305.11792", |
| "title": "Chain-of-thought prompting for responding to in-depth dialogue questions with LLM" |
| }, |
| "2306.04563": { |
| "arxivId": "2306.04563", |
| "title": "ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models" |
| }, |
| "2306.07622": { |
| "arxivId": "2306.07622", |
| "title": "Human-Like Intuitive Behavior and Reasoning Biases Emerged in Language Models - and Disappeared in GPT-4" |
| }, |
| "2303.12057": { |
| "arxivId": "2303.12057", |
| "title": "Large Language Models Can Be Used to Estimate the Ideologies of Politicians in a Zero-Shot Learning Setting" |
| }, |
| "2304.01457": { |
| "arxivId": "2304.01457", |
| "title": "Exploring Vision-Language Models for Imbalanced Learning" |
| }, |
| "2307.00112": { |
| "arxivId": "2307.00112", |
| "title": "Performance of ChatGPT on USMLE: Unlocking the Potential of Large Language Models for AI-Assisted Medical Education" |
| }, |
| "2306.08997": { |
| "arxivId": "2306.08997", |
| "title": "Exploring the MIT Mathematics and EECS Curriculum Using Large Language Models" |
| }, |
| "2305.14693": { |
| "arxivId": "2305.14693", |
| "title": "Have Large Language Models Developed a Personality?: Applicability of Self-Assessment Tests in Measuring Personality in LLMs" |
| }, |
| "2311.15296": { |
| "arxivId": "2311.15296", |
| "title": "UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation" |
| }, |
| "2305.11262": { |
| "arxivId": "2305.11262", |
| "title": "CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models" |
| }, |
| "2306.01590": { |
| "arxivId": "2306.01590", |
| "title": "An Evaluation of Log Parsing with ChatGPT" |
| }, |
| "2306.15261": { |
| "arxivId": "2306.15261", |
| "title": "A Survey on Out-of-Distribution Evaluation of Neural NLP Models" |
| }, |
| "2306.06264": { |
| "arxivId": "2306.06264", |
| "title": "Measuring and Modifying Factual Knowledge in Large Language Models" |
| }, |
| "2306.02864": { |
| "arxivId": "2306.02864", |
| "title": "Leveraging Large Language Models for Topic Classification in the Domain of Public Affairs" |
| }, |
| "2302.12297": { |
| "arxivId": "2302.12297", |
| "title": "Dynamic Benchmarking of Masked Language Models on Temporal Concept Drift with Multiple Views" |
| }, |
| "2306.02549": { |
| "arxivId": "2306.02549", |
| "title": "Evaluation of AI Chatbots for Patient-Specific EHR Questions" |
| }, |
| "2204.01906": { |
| "arxivId": "2204.01906", |
| "title": "Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks" |
| }, |
| "2306.01499": { |
| "arxivId": "2306.01499", |
| "title": "Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today" |
| }, |
| "2304.07849": { |
| "arxivId": "2304.07849", |
| "title": "ChatPLUG: Open-Domain Generative Dialogue System with Internet-Augmented Instruction Tuning for Digital Human" |
| }, |
| "2111.08181": { |
| "arxivId": "2111.08181", |
| "title": "Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair" |
| }, |
| "2305.12421": { |
| "arxivId": "2305.12421", |
| "title": "Evaluating Open Question Answering Evaluation" |
| }, |
| "2310.02174": { |
| "arxivId": "2310.02174", |
| "title": "Ask Again, Then Fail: Large Language Models' Vacillations in Judgement" |
| }, |
| "2309.11737": { |
| "arxivId": "2309.11737", |
| "title": "Choice-75: A Dataset on Decision Branching in Script Learning" |
| }, |
| "2305.15268": { |
| "arxivId": "2305.15268", |
| "title": "EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Models" |
| }, |
| "2306.04926": { |
| "arxivId": "2306.04926", |
| "title": "covLLM: Large Language Models for COVID-19 Biomedical Literature" |
| }, |
| "2306.04610": { |
| "arxivId": "2306.04610", |
| "title": "The Two Word Test: A Semantic Benchmark for Large Language Models" |
| } |
| } |
