Large Language Model Alignment: A Survey
Paper
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2309.15025
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Published
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2
LLM Refs
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Aligning Large Language Models with Human: A Survey
Paper • 2307.12966 • Published • 1 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
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SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
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LIMA: Less Is More for Alignment
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Aligning Large Language Models through Synthetic Feedback
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Generative Judge for Evaluating Alignment
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JudgeLM: Fine-tuned Large Language Models are Scalable Judges
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Quality-Diversity through AI Feedback
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
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Self-Consistency Improves Chain of Thought Reasoning in Language Models
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Fine-tuning Language Models with Generative Adversarial Feedback
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UltraFeedback: Boosting Language Models with High-quality Feedback
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Verbosity Bias in Preference Labeling by Large Language Models
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RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
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Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
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Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment
Paper • 2308.09662 • Published • 3 -
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
Paper • 2311.09528 • Published • 2 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 69 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 27 -
Reasons to Reject? Aligning Language Models with Judgments
Paper • 2312.14591 • Published • 17 -
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
Paper • 2308.07921 • Published • 22 -
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Paper • 2309.17452 • Published • 3 -
LLM Guided Inductive Inference for Solving Compositional Problems
Paper • 2309.11688 • Published • 1 -
A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
Paper • 2402.07927 • Published • 1 -
A Review of Sparse Expert Models in Deep Learning
Paper • 2209.01667 • Published • 3 -
The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey
Paper • 2401.07872 • Published • 2 -
Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs
Paper • 2309.03118 • Published • 2 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model
Paper • 2310.08072 • Published • 1 -
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering
Paper • 2309.06358 • Published • 1 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 40 -
A Comprehensive Analysis of Adapter Efficiency
Paper • 2305.07491 • Published • 1 -
Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs
Paper • 2304.14999 • Published • 2 -
Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification
Paper • 2308.07282 • Published • 1 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 30 -
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 45 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 46 -
MTEB: Massive Text Embedding Benchmark
Paper • 2210.07316 • Published • 6 -
Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data
Paper • 2306.13840 • Published • 11 -
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning
Paper • 2212.07919 • Published -
Llama 2: Open Foundation and Fine-Tuned Chat Models
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Training Verifiers to Solve Math Word Problems
Paper • 2110.14168 • Published • 4 -
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Paper • 1803.05457 • Published • 2 -
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
Paper • 1907.10641 • Published • 1 -
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Paper • 2206.04615 • Published • 5 -
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Paper • 2303.12712 • Published • 2 -
Deduplicating Training Data Makes Language Models Better
Paper • 2107.06499 • Published • 4 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
Oasis: Data Curation and Assessment System for Pretraining of Large Language Models
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LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 21 -
Reflexion: Language Agents with Verbal Reinforcement Learning
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GPT-4 Technical Report
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Beyond Language Models: Byte Models are Digital World Simulators
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Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
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