Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
Paper
• 2310.15123 • Published
• 8
CoT
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Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 19 -
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 • 2 -
Autonomous Tree-search Ability of Large Language Models
Paper • 2310.10686 • Published • 2 -
Tree-Planner: Efficient Close-loop Task Planning with Large Language Models
Paper • 2310.08582 • Published • 3 -
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
Paper • 2308.13259 • Published • 2 -
Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic
Paper • 2309.13339 • Published • 3 -
CodeCoT and Beyond: Learning to Program and Test like a Developer
Paper • 2308.08784 • Published • 5 -
Enhancing Reasoning Capabilities of Large Language Models: A Graph-Based Verification Approach
Paper • 2308.09267 • Published • 3 -
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 -
SteP: Stacked LLM Policies for Web Actions
Paper • 2310.03720 • Published • 8 -
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 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 80 -
SCREWS: A Modular Framework for Reasoning with Revisions
Paper • 2309.13075 • Published • 18 -
Forward-Backward Reasoning in Large Language Models for Mathematical Verification
Paper • 2308.07758 • Published • 4 -
LLM Guided Inductive Inference for Solving Compositional Problems
Paper • 2309.11688 • Published • 1 -
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Paper • 2309.05653 • Published • 10 -
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Paper • 2309.12284 • Published • 19 -
Reverse Chain: A Generic-Rule for LLMs to Master Multi-API Planning
Paper • 2310.04474 • Published • 2 -
Sci-CoT: Leveraging Large Language Models for Enhanced Knowledge Distillation in Small Models for Scientific QA
Paper • 2308.04679 • Published • 1 -
Retrieval-Generation Synergy Augmented Large Language Models
Paper • 2310.05149 • Published • 1 -
Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation
Paper • 2310.08395 • Published • 1 -
GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence
Paper • 2310.05388 • Published • 4 -
CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules
Paper • 2310.08992 • Published • 12 -
A Zero-Shot Language Agent for Computer Control with Structured Reflection
Paper • 2310.08740 • Published • 15 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 15 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 34 -
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning
Paper • 2309.04663 • Published • 6 -
Design of Chain-of-Thought in Math Problem Solving
Paper • 2309.11054 • Published • 2 -
Large Language Models Are Also Good Prototypical Commonsense Reasoners
Paper • 2309.13165 • Published • 1 -
Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs
Paper • 2309.03118 • Published • 2 -
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Paper • 2308.09729 • Published • 6 -
Commonsense Knowledge Transfer for Pre-trained Language Models
Paper • 2306.02388 • 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 • 14 -
Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models
Paper • 2309.12767 • Published • 1 -
Exploring the Integration Strategies of Retriever and Large Language Models
Paper • 2308.12574 • Published • 1 -
Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks
Paper • 2304.14732 • Published • 2 -
Improving Embedded Knowledge Graph Multi-hop Question Answering by introducing Relational Chain Reasoning
Paper • 2110.12679 • Published • 1 -
ControlLLM: Augment Language Models with Tools by Searching on Graphs
Paper • 2310.17796 • Published • 18 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 33 -
Query Expansion by Prompting Large Language Models
Paper • 2305.03653 • Published • 3 -
Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency
Paper • 2309.17382 • Published • 6 -
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 -
Small Language Models Improve Giants by Rewriting Their Outputs
Paper • 2305.13514 • Published • 2 -
Introspective Tips: Large Language Model for In-Context Decision Making
Paper • 2305.11598 • Published • 1 -
Tab-CoT: Zero-shot Tabular Chain of Thought
Paper • 2305.17812 • Published • 2 -
Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
Paper • 2211.12588 • Published • 3 -
Structured Chain-of-Thought Prompting for Code Generation
Paper • 2305.06599 • Published • 1 -
Improving ChatGPT Prompt for Code Generation
Paper • 2305.08360 • Published • 1 -
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting
Paper • 2305.07004 • Published • 1 -
Bridging Code Semantic and LLMs: Semantic Chain-of-Thought Prompting for Code Generation
Paper • 2310.10698 • Published • 2 -
Test-Case-Driven Programming Understanding in Large Language Models for Better Code Generation
Paper • 2309.16120 • Published • 1 -
Ada-Instruct: Adapting Instruction Generators for Complex Reasoning
Paper • 2310.04484 • Published • 5 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3 -
SelfzCoT: a Self-Prompt Zero-shot CoT from Semantic-level to Code-level for a Better Utilization of LLMs
Paper • 2305.11461 • Published • 1 -
Leveraging Training Data in Few-Shot Prompting for Numerical Reasoning
Paper • 2305.18170 • Published • 2 -
Learning Multi-Step Reasoning by Solving Arithmetic Tasks
Paper • 2306.01707 • Published • 2 -
Automatic Chain of Thought Prompting in Large Language Models
Paper • 2210.03493 • Published • 2 -
Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models
Paper • 2306.03799 • Published • 1 -
On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
Paper • 2212.08061 • Published • 1 -
Large Language Models are Better Reasoners with Self-Verification
Paper • 2212.09561 • Published • 1 -
Beyond Words: A Mathematical Framework for Interpreting Large Language Models
Paper • 2311.03033 • Published • 1 -
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Paper • 2311.04254 • Published • 15 -
Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
Paper • 2305.03268 • Published • 3 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 5 -
ThinkSum: Probabilistic reasoning over sets using large language models
Paper • 2210.01293 • Published • 1 -
Generating Efficient Training Data via LLM-based Attribute Manipulation
Paper • 2307.07099 • Published • 1 -
EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning
Paper • 2309.10687 • Published • 1 -
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
Paper • 2310.02304 • Published • 1 -
On the Planning, Search, and Memorization Capabilities of Large Language Models
Paper • 2309.01868 • Published • 1 -
Dynamic Planning with a LLM
Paper • 2308.06391 • Published • 2 -
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Paper • 2203.11171 • Published • 5 -
Cognitive Architectures for Language Agents
Paper • 2309.02427 • Published • 8 -
Contrastive Chain-of-Thought Prompting
Paper • 2311.09277 • Published • 35 -
Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
Paper • 2311.09210 • Published • 2 -
PathFinder: Guided Search over Multi-Step Reasoning Paths
Paper • 2312.05180 • Published • 10 -
Training Chain-of-Thought via Latent-Variable Inference
Paper • 2312.02179 • Published • 10 -
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
Paper • 2312.04474 • Published • 34 -
Thread of Thought Unraveling Chaotic Contexts
Paper • 2311.08734 • Published • 7 -
Fast Chain-of-Thought: A Glance of Future from Parallel Decoding Leads to Answers Faster
Paper • 2311.08263 • Published • 16 -
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning
Paper • 2310.16049 • Published • 5 -
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Paper • 2401.04398 • Published • 25 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 21 -
ADaPT: As-Needed Decomposition and Planning with Language Models
Paper • 2311.05772 • Published • 12 -
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Paper • 2308.00436 • Published • 24 -
Better Zero-Shot Reasoning with Role-Play Prompting
Paper • 2308.07702 • Published • 3 -
Augmenting Math Word Problems via Iterative Question Composing
Paper • 2401.09003 • Published • 2 -
xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning
Paper • 2401.07037 • Published • 2 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 46 -
Prompting-based Synthetic Data Generation for Few-Shot Question Answering
Paper • 2405.09335 • Published -
Chain-of-Instructions: Compositional Instruction Tuning on Large Language Models
Paper • 2402.11532 • Published • 1 -
Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models
Paper • 2407.03181 • Published • 1 -
Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding
Paper • 2409.08561 • Published -
RLP: Reinforcement as a Pretraining Objective
Paper • 2510.01265 • Published • 44