conftrace_

Jungwook Choi

17 papers · 2018–2026 · 7 conferences · across top CS/AI conferences

Achievements

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+7 more ↓ πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (7) 🌍 Conference Polyglot (7) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (31)
πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (31) 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (65) πŸ’Ž Century Club (16) πŸ”₯ Unstoppable (5)

Conferences

NIPS (4) ACL (3) EMNLP (3) AAAI (2) EACL (2) ICLR (2) ICCV (1)

Papers

MapCoder-Lite: Distilling Multi-Agent Coding into a Single Small LLM EACL 2026 AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference ACL 2025 RILQ: Rank-Insensitive LoRA-Based Quantization Error Compensation for Boosting 2-Bit Large Language Model Accuracy AAAI 2025 Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control ICCV 2025 RA-LoRA: Rank-Adaptive Parameter-Efficient Fine-Tuning for Accurate 2-bit Quantized Large Language Models ACL 2024 InfiniPot: Infinite Context Processing on Memory-Constrained LLMs EMNLP 2024 Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment ACL 2024 Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization EMNLP 2023 Token-Scaled Logit Distillation for Ternary Weight Generative Language Models NIPS 2023 Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers EACL 2023 SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots NIPS 2023 Understanding and Improving Knowledge Distillation for Quantization Aware Training of Large Transformer Encoders EMNLP 2022 Understanding the Role of Self Attention for Efficient Speech Recognition ICLR 2022 Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks AAAI 2021 Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks NIPS 2019 Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks ICLR 2019 Training Deep Neural Networks with 8-bit Floating Point Numbers NIPS 2018