← Optimization & Theory
Machine Learning › Optimization & Theory ›

Neural Network Optimization

3648 directly classified papers

Papers per year

Papers

Rethinking the Role of Text Complexity in Language Model Pretraining EMNLP 2025
UniMath-CoT: A Unified Framework for Multimodal Mathematical Reasoning with Re-Inference Affirmation EMNLP 2025
Disentangling Mathematical Reasoning in LLMs: A Methodological Investigation of Internal Mechanisms EMNLP 2025
Think Clearly: Improving Reasoning via Redundant Token Pruning EMNLP 2025
SwiftPrune: Hessian-Free Weight Pruning for Large Language Models EMNLP 2025
Language Models Can Easily Learn to Reason from Demonstrations EMNLP 2025
Prejudge-Before-Think: Enhancing Large Language Models at Test-Time by Process Prejudge Reasoning EMNLP 2025
Training compute-optimal transformer encoder models EMNLP 2025
Fin-ExBERT: User Intent based Text Extraction in Financial Context using Graph-Augmented BERT and trainable Plugin EMNLP 2025
TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use EMNLP 2025
How Does DPO Reduce Toxicity? A Mechanistic Neuron-Level Analysis EMNLP 2025
ThinkTuning: Instilling Cognitive Reflections without Distillation EMNLP 2025
E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning EMNLP 2025
AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training EMNLP 2025
Towards Infinite-Long Prefix in Transformer EMNLP 2025
MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm ICCV 2025
iTool: Reinforced Fine-Tuning with Dynamic Deficiency Calibration for Advanced Tool Use EMNLP 2025
MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper EMNLP 2025
Breaking the Attention Trap in Code LLMs: A Rejection Sampling Approach to Enhance Code Execution Prediction EMNLP 2025
ModRWKV: Transformer Multimodality in Linear Time EMNLP 2025
ECHO-LLaMA: Efficient Caching for High-Performance LLaMA Training EMNLP 2025
DINT Transformer EMNLP 2025
Exploring smaller batch sizes for a high-performing BabyLM model architecture EMNLP 2025
Memory-Efficient Backpropagation for Fine-Tuning LLMs on Resource-Constrained Mobile Devices EMNLP 2025
s1: Simple test-time scaling EMNLP 2025