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Large Language Models

2678 directly classified papers

Papers per year

Papers

An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding NIPS 2024
DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution NIPS 2024
Causal language modeling can elicit search and reasoning capabilities on logic puzzles NIPS 2024
UniAudio 1.5: Large Language Model-Driven Audio Codec is A Few-Shot Audio Task Learner NIPS 2024
Vript: A Video Is Worth Thousands of Words NIPS 2024
CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models NIPS 2024
The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data NIPS 2024
To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty NIPS 2024
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection NIPS 2024
Vision-Language Models are Strong Noisy Label Detectors NIPS 2024
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming NIPS 2024
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models NIPS 2024
QTIP: Quantization with Trellises and Incoherence Processing NIPS 2024
Coupled Mamba: Enhanced Multimodal Fusion with Coupled State Space Model NIPS 2024
Are Language Models Actually Useful for Time Series Forecasting? NIPS 2024
Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models NIPS 2024
How Do Large Language Models Acquire Factual Knowledge During Pretraining? NIPS 2024
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance NIPS 2024
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs NIPS 2024
SelfCodeAlign: Self-Alignment for Code Generation NIPS 2024
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning NIPS 2024
Self-Retrieval: End-to-End Information Retrieval with One Large Language Model NIPS 2024
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models NIPS 2024
Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters NIPS 2024
Co-occurrence is not Factual Association in Language Models NIPS 2024