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Collections including paper arxiv:2402.00858

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 7 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Prompt Engineering - InContext Learning

The Prompt Report: A Systematic Survey of Prompting Techniques

Paper • 2406.06608 • Published Jun 6, 2024 • 68
In-Context Principle Learning from Mistakes

Paper • 2402.05403 • Published Feb 8, 2024 • 17
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23

InContext Learning

In-Context Language Learning: Architectures and Algorithms

Paper • 2401.12973 • Published Jan 23, 2024 • 4
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 14
Emergence of Abstractions: Concept Encoding and Decoding Mechanism for In-Context Learning in Transformers

Paper • 2412.12276 • Published Dec 16, 2024 • 15

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Paper • 2401.15688 • Published Jan 28, 2024 • 11
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26, 2024 • 73
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Paper • 2401.15071 • Published Jan 26, 2024 • 37

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10, 2024 • 18

Contextual understanding

Supervised Knowledge Makes Large Language Models Better In-context Learners

Paper • 2312.15918 • Published Dec 26, 2023 • 9
Make Your LLM Fully Utilize the Context

Paper • 2404.16811 • Published Apr 25, 2024 • 55
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 21
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Specialized Language Models with Cheap Inference from Limited Domain Data

Paper • 2402.01093 • Published Feb 2, 2024 • 47
Premise Order Matters in Reasoning with Large Language Models

Paper • 2402.08939 • Published Feb 14, 2024 • 28

OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Efficient Exploration for LLMs

Paper • 2402.00396 • Published Feb 1, 2024 • 22
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Transforming and Combining Rewards for Aligning Large Language Models

Paper • 2402.00742 • Published Feb 1, 2024 • 12

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Paper • 2408.08152 • Published Aug 15, 2024 • 60
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23, 2024 • 20
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 56
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 20

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 7 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Contextual understanding

Supervised Knowledge Makes Large Language Models Better In-context Learners

Paper • 2312.15918 • Published Dec 26, 2023 • 9
Make Your LLM Fully Utilize the Context

Paper • 2404.16811 • Published Apr 25, 2024 • 55
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23

Prompt Engineering - InContext Learning

The Prompt Report: A Systematic Survey of Prompting Techniques

Paper • 2406.06608 • Published Jun 6, 2024 • 68
In-Context Principle Learning from Mistakes

Paper • 2402.05403 • Published Feb 8, 2024 • 17
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 21
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

InContext Learning

In-Context Language Learning: Architectures and Algorithms

Paper • 2401.12973 • Published Jan 23, 2024 • 4
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 14
Emergence of Abstractions: Concept Encoding and Decoding Mechanism for In-Context Learning in Transformers

Paper • 2412.12276 • Published Dec 16, 2024 • 15

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Specialized Language Models with Cheap Inference from Limited Domain Data

Paper • 2402.01093 • Published Feb 2, 2024 • 47
Premise Order Matters in Reasoning with Large Language Models

Paper • 2402.08939 • Published Feb 14, 2024 • 28

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Paper • 2401.15688 • Published Jan 28, 2024 • 11
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26, 2024 • 73
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Paper • 2401.15071 • Published Jan 26, 2024 • 37

OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Efficient Exploration for LLMs

Paper • 2402.00396 • Published Feb 1, 2024 • 22
Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Transforming and Combining Rewards for Aligning Large Language Models

Paper • 2402.00742 • Published Feb 1, 2024 • 12

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10, 2024 • 18

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Paper • 2408.08152 • Published Aug 15, 2024 • 60
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23, 2024 • 20
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 56
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 20

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