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Collections including paper arxiv:2311.06158

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 1
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

Paper • 2308.13259 • Published Aug 25, 2023 • 2
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

Paper • 2309.05653 • Published Sep 11, 2023 • 10
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Paper • 2309.12284 • Published Sep 21, 2023 • 19

Ada-Instruct: Adapting Instruction Generators for Complex Reasoning

Paper • 2310.04484 • Published Oct 6, 2023 • 5
Diversity of Thought Improves Reasoning Abilities of Large Language Models

Paper • 2310.07088 • Published Oct 11, 2023 • 5
Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 77
Democratizing Reasoning Ability: Tailored Learning from Large Language Model

Paper • 2310.13332 • Published Oct 20, 2023 • 14

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 104
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 40
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 19
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 36

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

Paper • 2309.12307 • Published Sep 21, 2023 • 88
NEFTune: Noisy Embeddings Improve Instruction Finetuning

Paper • 2310.05914 • Published Oct 9, 2023 • 14
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Paper • 2312.15166 • Published Dec 23, 2023 • 56
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon

Paper • 2401.03462 • Published Jan 7, 2024 • 27

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Paper • 2401.02954 • Published Jan 5, 2024 • 41
Qwen Technical Report

Paper • 2309.16609 • Published Sep 28, 2023 • 35
GPT-4 Technical Report

Paper • 2303.08774 • Published Mar 15, 2023 • 5
Gemini: A Family of Highly Capable Multimodal Models

Paper • 2312.11805 • Published Dec 19, 2023 • 44

Solver training

Language Models can be Logical Solvers

Paper • 2311.06158 • Published Nov 10, 2023 • 18
SymbolicAI: A framework for logic-based approaches combining generative models and solvers

Paper • 2402.00854 • Published Feb 1, 2024 • 19
Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 67
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

Paper • 2402.14083 • Published Feb 21, 2024 • 47

logical reasoning with llms

Language Models can be Logical Solvers

Paper • 2311.06158 • Published Nov 10, 2023 • 18
Fusion-Eval: Integrating Evaluators with LLMs

Paper • 2311.09204 • Published Nov 15, 2023 • 5
Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation

Paper • 2311.08877 • Published Nov 15, 2023 • 6
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?

Paper • 2311.07587 • Published Nov 8, 2023 • 3

Language Models can be Logical Solvers

Paper • 2311.06158 • Published Nov 10, 2023 • 18

Language Models can be Logical Solvers

Paper • 2311.06158 • Published Nov 10, 2023 • 18

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