conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Neural Network Optimization

3,648 papers

Papers per year

Papers

Initialization of Large Language Models via Reparameterization to Mitigate Loss Spikes EMNLP 2024
QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning EMNLP 2024
Make Large Language Model a Better Ranker EMNLP 2024
Tokenization Falling Short: On Subword Robustness in Large Language Models EMNLP 2024
Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models EMNLP 2024
Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology EMNLP 2024
Draft on the Fly: Adaptive Self-Speculative Decoding using Cosine Similarity EMNLP 2024
In-Context Former: Lightning-fast Compressing Context for Large Language Model EMNLP 2024
Ruler: A Model-Agnostic Method to Control Generated Length for Large Language Models EMNLP 2024
Tending Towards Stability: Convergence Challenges in Small Language Models EMNLP 2024
Revisiting Catastrophic Forgetting in Large Language Model Tuning EMNLP 2024
Normalized Narrow Jump To Conclusions: Normalized Narrow Shortcuts for Parameter Efficient Early Exit Transformer Prediction EMNLP 2024
On the token distance modeling ability of higher RoPE attention dimension EMNLP 2024
Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection EMNLP 2024
SCA: Selective Compression Attention for Efficiently Extending the Context Window of Large Language Models EMNLP 2024
DAdEE: Unsupervised Domain Adaptation in Early Exit PLMs EMNLP 2024
LongHeads: Multi-Head Attention is Secretly a Long Context Processor EMNLP 2024
LPZero: Language Model Zero-cost Proxy Search from Zero EMNLP 2024
Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs. EMNLP 2024
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation EMNLP 2024
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs EMNLP 2024
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models EMNLP 2024
Auto-Evolve: Enhancing Large Language Model’s Performance via Self-Reasoning Framework EMNLP 2024
Unlocking Black-Box Prompt Tuning Efficiency via Zeroth-Order Optimization EMNLP 2024
Hop, skip, jump to Convergence: Dynamics of Learning Rate Transitions for Improved Training of Large Language Models EMNLP 2024