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Collections including paper arxiv:2407.00320

Unlocking Continual Learning Abilities in Language Models

Paper • 2406.17245 • Published Jun 25 • 28
A Closer Look into Mixture-of-Experts in Large Language Models

Paper • 2406.18219 • Published Jun 26 • 15
Symbolic Learning Enables Self-Evolving Agents

Paper • 2406.18532 • Published Jun 26 • 10
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs

Paper • 2406.18629 • Published Jun 26 • 40

Eliminating Position Bias of Language Models: A Mechanistic Approach

Paper • 2407.01100 • Published Jul 1 • 6
To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models

Paper • 2407.01920 • Published Jul 2 • 13
LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37

Papers - Training - Brier Score - Probabilistic Accuracy

LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37

Papers - Math - TabMWP

LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37

Planning-with-LLM

Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26 • 47
Adaptable Logical Control for Large Language Models

Paper • 2406.13892 • Published Jun 19 • 1
SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation

Paper • 2406.19215 • Published Jun 27 • 29
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models

Paper • 2405.14831 • Published May 23 • 3

ashawkey/LGM

Text-to-3D • Updated Jun 3 • 106
LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37
DogeRM: Equipping Reward Models with Domain Knowledge through Model Merging

Paper • 2407.01470 • Published Jul 1 • 5

How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Paper • 2406.11813 • Published Jun 17 • 29
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries

Paper • 2406.12824 • Published Jun 18 • 20
Tokenization Falling Short: The Curse of Tokenization

Paper • 2406.11687 • Published Jun 17 • 15
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level

Paper • 2406.11817 • Published Jun 17 • 13

Relevant-Papers-Midterm

Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models

Paper • 2402.14848 • Published Feb 19 • 18
The Prompt Report: A Systematic Survey of Prompting Techniques

Paper • 2406.06608 • Published Jun 6 • 52
CRAG -- Comprehensive RAG Benchmark

Paper • 2406.04744 • Published Jun 7 • 40
Transformers meet Neural Algorithmic Reasoners

Paper • 2406.09308 • Published Jun 13 • 43

Papers - Llama 3 - Fine-tuning

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 43
LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 47
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18 • 53
SnapKV: LLM Knows What You are Looking for Before Generation

Paper • 2404.14469 • Published Apr 22 • 23
FlowMind: Automatic Workflow Generation with LLMs

Paper • 2404.13050 • Published Mar 17 • 32

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