Top Important LLM Papers for the Week from 01/01 to 07/01

Stay Updated with Recent Large Language Models Research

Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article summarizes some of the most important LLM papers published during the first week of January.

The papers cover various topics shaping the next generation of language models, from model optimization and scaling to reasoning, benchmarking, and enhancing performance. Keeping up with novel LLM research across these domains will help guide continued progress toward models that are more capable, robust, and aligned with human values.

Table of Contents:

1. LLM Progress & Benchmarking

2. LLM Fine Tuning

3. LLM Reasoning

4. LLM Training & Evaluation

5. Transformers & Attention Based Models

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1. LLM Progress & Benchmarking

1. Boosting Large Language Model for Speech Synthesis: An Empirical Study

2. LARP: Language-Agent Role Play for Open-World Games

3. Improving Text Embeddings with Large Language Models

4. PanGu-$π$: Enhancing Language Model Architectures via Nonlinearity Compensation

5. COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training

6. TinyLlama: An Open-Source Small Language Model

7. GeoGalactica: A Scientific Large Language Model in Geoscience

8. Unicron: Economizing Self-Healing LLM Training at Scale

9. LLaMA Beyond English: An Empirical Study on Language Capability Transfer

10. DocLLM: A layout-aware generative language model for multimodal document understanding

11. LLaMA Pro: Progressive LLaMA with Block Expansion

12. LLM Augmented LLMs: Expanding Capabilities through Composition

13. LLaVA-$φ$: Efficient Multi-Modal Assistant with Small Language Model

14. A Comprehensive Study of Knowledge Editing for Large Language Models

2. LLM Fine Tuning

1. Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

2. Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models

3. LLM Reasoning

1. Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers

2. Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language Models

4. LLM Training & Evaluation

1. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws

2. Understanding LLMs: A Comprehensive Overview from Training to Inference

5. Transformers & Attention Based Models

1. Boundary Attention: Learning to Find Faint Boundaries at Any Resolution

2. ICE-GRT: Instruction Context Enhancement by Generative Reinforcement-based Transformers

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