Ada-Instruct: Adapting Instruction Generators for Complex Reasoning
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2310.04484
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Published
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5
Reasoning
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Diversity of Thought Improves Reasoning Abilities of Large Language Models
Paper • 2310.07088 • Published • 5 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Paper • 2310.13332 • Published • 14 -
Teaching Language Models to Self-Improve through Interactive Demonstrations
Paper • 2310.13522 • Published • 11 -
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection
Paper • 2310.05035 • Published • 1 -
Chain-of-Thought Reasoning is a Policy Improvement Operator
Paper • 2309.08589 • Published • 1 -
MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language Models
Paper • 2310.12426 • Published • 1 -
Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning
Paper • 2310.11716 • Published • 5 -
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Paper • 2310.04406 • Published • 8 -
Autonomous Tree-search Ability of Large Language Models
Paper • 2310.10686 • Published • 2 -
Adapting LLM Agents Through Communication
Paper • 2310.01444 • Published • 3 -
Large Language Models Are Also Good Prototypical Commonsense Reasoners
Paper • 2309.13165 • Published • 1 -
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models
Paper • 2310.05074 • Published • 1 -
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
Paper • 2308.13259 • Published • 2 -
SmartPlay : A Benchmark for LLMs as Intelligent Agents
Paper • 2310.01557 • Published • 12 -
Large Language Models as Analogical Reasoners
Paper • 2310.01714 • Published • 15 -
Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic
Paper • 2309.13339 • Published • 2 -
CodeCoT and Beyond: Learning to Program and Test like a Developer
Paper • 2308.08784 • Published • 5 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 33 -
Enhancing Reasoning Capabilities of Large Language Models: A Graph-Based Verification Approach
Paper • 2308.09267 • Published • 2 -
Are Human-generated Demonstrations Necessary for In-context Learning?
Paper • 2309.14681 • Published • 1 -
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Paper • 2310.03710 • Published • 2 -
Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
Paper • 2310.00280 • Published • 3 -
SELF: Language-Driven Self-Evolution for Large Language Model
Paper • 2310.00533 • Published • 2 -
SteP: Stacked LLM Policies for Web Actions
Paper • 2310.03720 • Published • 7 -
You Only Look at Screens: Multimodal Chain-of-Action Agents
Paper • 2309.11436 • Published • 1 -
Instance Needs More Care: Rewriting Prompts for Instances Yields Better Zero-Shot Performance
Paper • 2310.02107 • Published • 3 -
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
Paper • 2309.10691 • Published • 4 -
Lemur: Harmonizing Natural Language and Code for Language Agents
Paper • 2310.06830 • Published • 30 -
EcoAssistant: Using LLM Assistant More Affordably and Accurately
Paper • 2310.03046 • Published • 5 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 73 -
A Long Way to Go: Investigating Length Correlations in RLHF
Paper • 2310.03716 • Published • 9 -
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Paper • 2310.03094 • Published • 12 -
SCREWS: A Modular Framework for Reasoning with Revisions
Paper • 2309.13075 • Published • 15 -
Forward-Backward Reasoning in Large Language Models for Mathematical Verification
Paper • 2308.07758 • Published • 4 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 30 -
Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning
Paper • 2309.10814 • Published • 3 -
LLM Guided Inductive Inference for Solving Compositional Problems
Paper • 2309.11688 • Published • 1 -
AskIt: Unified Programming Interface for Programming with Large Language Models
Paper • 2308.15645 • Published • 2 -
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Paper • 2309.12284 • Published • 18 -
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Paper • 2309.17452 • Published • 3 -
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
Paper • 2308.07921 • Published • 22 -
Retrieval-Generation Synergy Augmented Large Language Models
Paper • 2310.05149 • Published • 1 -
GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence
Paper • 2310.05388 • Published • 4 -
The Consensus Game: Language Model Generation via Equilibrium Search
Paper • 2310.09139 • Published • 12 -
CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization
Paper • 2310.10134 • Published • 1 -
When can transformers reason with abstract symbols?
Paper • 2310.09753 • Published • 2 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 10 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 32 -
In-Context Pretraining: Language Modeling Beyond Document Boundaries
Paper • 2310.10638 • Published • 28 -
Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
Paper • 2310.15123 • Published • 7 -
Re-Reading Improves Reasoning in Language Models
Paper • 2309.06275 • Published • 3 -
SkyMath: Technical Report
Paper • 2310.16713 • Published • 2 -
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model
Paper • 2212.09146 • Published • 3 -
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks
Paper • 2305.18395 • Published • 1 -
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
Paper • 2304.11477 • Published • 3 -
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Paper • 2308.09729 • Published • 4 -
Natural Logic-guided Autoregressive Multi-hop Document Retrieval for Fact Verification
Paper • 2212.05276 • Published • 1 -
Prompt Engineering and Calibration for Zero-Shot Commonsense Reasoning
Paper • 2304.06962 • Published • 1 -
Commonsense Knowledge Transfer for Pre-trained Language Models
Paper • 2306.02388 • Published • 1 -
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Paper • 2110.07178 • Published • 1 -
Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model
Paper • 2306.10241 • Published • 1 -
CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering
Paper • 2305.14869 • Published • 1 -
Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering
Paper • 2305.05936 • Published • 1 -
ALERT: Adapting Language Models to Reasoning Tasks
Paper • 2212.08286 • Published • 2 -
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
Paper • 2305.11554 • Published • 2 -
GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution
Paper • 2307.08775 • Published • 1 -
ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models
Paper • 2305.18323 • Published • 1 -
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models
Paper • 2304.09842 • Published • 1 -
T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Large Language Model Signals for Science Question Answering
Paper • 2305.03453 • Published • 1 -
Question Decomposition Improves the Faithfulness of Model-Generated Reasoning
Paper • 2307.11768 • Published • 12 -
Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models
Paper • 2309.12767 • Published • 1 -
Complex Logical Reasoning over Knowledge Graphs using Large Language Models
Paper • 2305.01157 • Published • 1 -
ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning
Paper • 2309.01538 • Published • 2 -
Visual Programming: Compositional visual reasoning without training
Paper • 2211.11559 • Published • 1 -
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems
Paper • 2210.15037 • Published • 1 -
Better Zero-Shot Reasoning with Role-Play Prompting
Paper • 2308.07702 • Published • 2 -
How FaR Are Large Language Models From Agents with Theory-of-Mind?
Paper • 2310.03051 • Published • 34 -
TeacherLM: Teaching to Fish Rather Than Giving the Fish, Language Modeling Likewise
Paper • 2310.19019 • Published • 9 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 14 -
RRAML: Reinforced Retrieval Augmented Machine Learning
Paper • 2307.12798 • Published • 1 -
Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency
Paper • 2309.17382 • Published • 4 -
Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach
Paper • 2306.03604 • Published • 1 -
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models
Paper • 2305.18507 • Published • 1 -
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting
Paper • 2306.06427 • Published • 2 -
Progressive-Hint Prompting Improves Reasoning in Large Language Models
Paper • 2304.09797 • Published • 1 -
Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
Paper • 2211.12588 • Published • 3 -
Natural Language Reasoning, A Survey
Paper • 2303.14725 • Published • 1 -
A Zero-Shot Language Agent for Computer Control with Structured Reflection
Paper • 2310.08740 • Published • 14 -
ExpeL: LLM Agents Are Experiential Learners
Paper • 2308.10144 • Published • 2 -
TART: A plug-and-play Transformer module for task-agnostic reasoning
Paper • 2306.07536 • Published • 11 -
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 37 -
Reasoning with Language Model Prompting: A Survey
Paper • 2212.09597 • Published • 2 -
Learning Multi-Step Reasoning by Solving Arithmetic Tasks
Paper • 2306.01707 • Published • 1 -
Tailoring Self-Rationalizers with Multi-Reward Distillation
Paper • 2311.02805 • Published • 3 -
Integrating Graphs with Large Language Models: Methods and Prospects
Paper • 2310.05499 • Published • 1 -
Making Large Language Models Better Reasoners with Alignment
Paper • 2309.02144 • Published • 2 -
Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Paper • 2308.01825 • Published • 21 -
Beyond Words: A Mathematical Framework for Interpreting Large Language Models
Paper • 2311.03033 • Published • 1 -
Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Paper • 2311.04205 • Published • 5 -
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Paper • 2311.04254 • Published • 13 -
Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
Paper • 2305.03268 • Published • 2 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 4 -
ThinkSum: Probabilistic reasoning over sets using large language models
Paper • 2210.01293 • Published • 1 -
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought
Paper • 2306.12672 • Published • 26 -
Language Models can be Logical Solvers
Paper • 2311.06158 • Published • 18 -
LLM Cognitive Judgements Differ From Human
Paper • 2307.11787 • Published • 1 -
When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust
Paper • 2305.07230 • Published • 1 -
Unifying Large Language Models and Knowledge Graphs: A Roadmap
Paper • 2306.08302 • Published • 3 -
Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners
Paper • 2305.14825 • Published • 1 -
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
Paper • 2306.09841 • Published • 2 -
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Paper • 2203.11171 • Published • 1 -
Semantic Consistency for Assuring Reliability of Large Language Models
Paper • 2308.09138 • Published • 2 -
Introspective Tips: Large Language Model for In-Context Decision Making
Paper • 2305.11598 • Published • 1 -
Cognitive Architectures for Language Agents
Paper • 2309.02427 • Published • 8 -
SPRING: GPT-4 Out-performs RL Algorithms by Studying Papers and Reasoning
Paper • 2305.15486 • Published • 1 -
Contrastive Chain-of-Thought Prompting
Paper • 2311.09277 • Published • 34 -
Flows: Building Blocks of Reasoning and Collaborating AI
Paper • 2308.01285 • Published • 2 -
System 2 Attention (is something you might need too)
Paper • 2311.11829 • Published • 39 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 35 -
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Paper • 2311.11315 • Published • 6 -
PathFinder: Guided Search over Multi-Step Reasoning Paths
Paper • 2312.05180 • Published • 9 -
REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization
Paper • 2310.14418 • Published • 1 -
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents
Paper • 2312.01279 • Published • 3 -
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
Paper • 2312.04474 • Published • 29 -
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations
Paper • 2311.08469 • Published • 10 -
Thread of Thought Unraveling Chaotic Contexts
Paper • 2311.08734 • Published • 6 -
The ART of LLM Refinement: Ask, Refine, and Trust
Paper • 2311.07961 • Published • 10 -
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 19 -
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning
Paper • 2310.16049 • Published • 4 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 10 -
SUR-adapter: Enhancing Text-to-Image Pre-trained Diffusion Models with Large Language Models
Paper • 2305.05189 • Published • 2 -
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Paper • 2401.04398 • Published • 20 -
Bridging Code Semantic and LLMs: Semantic Chain-of-Thought Prompting for Code Generation
Paper • 2310.10698 • Published • 1 -
ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models
Paper • 2401.13311 • Published • 10 -
K-Level Reasoning with Large Language Models
Paper • 2402.01521 • Published • 17 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16 -
Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval
Paper • 2308.04711 • Published • 1 -
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Paper • 2308.00436 • Published • 21 -
Large Language Models are Better Reasoners with Self-Verification
Paper • 2212.09561 • Published • 1 -
Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language Models
Paper • 2305.15074 • Published • 1 -
Metacognitive Prompting Improves Understanding in Large Language Models
Paper • 2308.05342 • Published • 2 -
LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding
Paper • 2306.14924 • Published • 2 -
Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations
Paper • 2311.05584 • Published • 1 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 30 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 27 -
PyReason: Software for Open World Temporal Logic
Paper • 2302.13482 • Published -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 72 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 47 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 44