Saved in:
| Main Authors: | Hwang, Jaehui, Han, Dongyoon, Yun, Sangdoo, Heo, Byeongho |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.17421 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
What Defines Good Reasoning in LLMs? Dissecting Reasoning Steps with Multi-Aspect Evaluation
by: Do, Heejin, et al.
Published: (2025)
by: Do, Heejin, et al.
Published: (2025)
Token Bottleneck: One Token to Remember Dynamics
by: Kim, Taekyung, et al.
Published: (2025)
by: Kim, Taekyung, et al.
Published: (2025)
Rotary Position Embedding for Vision Transformer
by: Heo, Byeongho, et al.
Published: (2024)
by: Heo, Byeongho, et al.
Published: (2024)
Masking meets Supervision: A Strong Learning Alliance
by: Heo, Byeongho, et al.
Published: (2023)
by: Heo, Byeongho, et al.
Published: (2023)
RL makes MLLMs see better than SFT
by: Song, Junha, et al.
Published: (2025)
by: Song, Junha, et al.
Published: (2025)
Match me if you can: Semi-Supervised Semantic Correspondence Learning with Unpaired Images
by: Kim, Jiwon, et al.
Published: (2023)
by: Kim, Jiwon, et al.
Published: (2023)
Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction
by: Kim, Jang-Hyun, et al.
Published: (2026)
by: Kim, Jang-Hyun, et al.
Published: (2026)
Similarity of Neural Architectures using Adversarial Attack Transferability
by: Hwang, Jaehui, et al.
Published: (2022)
by: Hwang, Jaehui, et al.
Published: (2022)
Morphing Tokens Draw Strong Masked Image Models
by: Kim, Taekyung, et al.
Published: (2023)
by: Kim, Taekyung, et al.
Published: (2023)
Learning to See What You Need: Gaze Attention for Multimodal Large Language Models
by: Song, Junha, et al.
Published: (2026)
by: Song, Junha, et al.
Published: (2026)
Learning with Unmasked Tokens Drives Stronger Vision Learners
by: Kim, Taekyung, et al.
Published: (2023)
by: Kim, Taekyung, et al.
Published: (2023)
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs
by: Kim, Donghyun, et al.
Published: (2024)
by: Kim, Donghyun, et al.
Published: (2024)
MuCo: Multi-turn Contrastive Learning for Multimodal Embedding Model
by: Gu, Geonmo, et al.
Published: (2026)
by: Gu, Geonmo, et al.
Published: (2026)
Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models
by: Lee, Jung Hyun, et al.
Published: (2024)
by: Lee, Jung Hyun, et al.
Published: (2024)
SeiT++: Masked Token Modeling Improves Storage-efficient Training
by: Lee, Minhyun, et al.
Published: (2023)
by: Lee, Minhyun, et al.
Published: (2023)
DNNs May Determine Major Properties of Their Outputs Early, with Timing Possibly Driven by Bias
by: Park, Song, et al.
Published: (2025)
by: Park, Song, et al.
Published: (2025)
Model Stock: All we need is just a few fine-tuned models
by: Jang, Dong-Hwan, et al.
Published: (2024)
by: Jang, Dong-Hwan, et al.
Published: (2024)
Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency
by: Wang, Chenlong, et al.
Published: (2025)
by: Wang, Chenlong, et al.
Published: (2025)
StoryCoder: Narrative Reformulation for Structured Reasoning in LLM Code Generation
by: Jang, Geonhui, et al.
Published: (2026)
by: Jang, Geonhui, et al.
Published: (2026)
Exploring Conditions for Diffusion models in Robotic Control
by: Shin, Heeseong, et al.
Published: (2025)
by: Shin, Heeseong, et al.
Published: (2025)
MaskRIS: Semantic Distortion-aware Data Augmentation for Referring Image Segmentation
by: Lee, Minhyun, et al.
Published: (2024)
by: Lee, Minhyun, et al.
Published: (2024)
Toward Interactive Regional Understanding in Vision-Large Language Models
by: Lee, Jungbeom, et al.
Published: (2024)
by: Lee, Jungbeom, et al.
Published: (2024)
HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts
by: Kim, Wonjae, et al.
Published: (2024)
by: Kim, Wonjae, et al.
Published: (2024)
Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
by: Green, Tommaso, et al.
Published: (2025)
by: Green, Tommaso, et al.
Published: (2025)
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
by: Oh, Changdae, et al.
Published: (2024)
by: Oh, Changdae, et al.
Published: (2024)
Persona Prompting as a Lens on LLM Social Reasoning
by: Yang, Jing, et al.
Published: (2026)
by: Yang, Jing, et al.
Published: (2026)
Dr.LLM: Dynamic Layer Routing in LLMs
by: Heakl, Ahmed, et al.
Published: (2025)
by: Heakl, Ahmed, et al.
Published: (2025)
From Loops to Oops: Fallback Behaviors of Language Models Under Uncertainty
by: Ivgi, Maor, et al.
Published: (2024)
by: Ivgi, Maor, et al.
Published: (2024)
Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability
by: Lin, Zicheng, et al.
Published: (2024)
by: Lin, Zicheng, et al.
Published: (2024)
Token-Budget-Aware LLM Reasoning
by: Han, Tingxu, et al.
Published: (2024)
by: Han, Tingxu, et al.
Published: (2024)
When to Ensemble: Identifying Token-Level Points for Stable and Fast LLM Ensembling
by: Yun, Heecheol, et al.
Published: (2025)
by: Yun, Heecheol, et al.
Published: (2025)
Error as a Lens: Probing LLM Reasoning through Synthetic Misconception Generation
by: Yang, Xinming, et al.
Published: (2026)
by: Yang, Xinming, et al.
Published: (2026)
Token-Level Marginalization for Multi-Label LLM Classifiers
by: Praharaj, Anjaneya, et al.
Published: (2025)
by: Praharaj, Anjaneya, et al.
Published: (2025)
Extending Token Computation for LLM Reasoning
by: Liao, Bingli, et al.
Published: (2024)
by: Liao, Bingli, et al.
Published: (2024)
Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
by: Goel, Anmol, et al.
Published: (2026)
by: Goel, Anmol, et al.
Published: (2026)
Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning
by: Liu, Hanbing, et al.
Published: (2025)
by: Liu, Hanbing, et al.
Published: (2025)
Cross-Tokenizer LLM Distillation through a Byte-Level Interface
by: Singh, Avyav Kumar, et al.
Published: (2026)
by: Singh, Avyav Kumar, et al.
Published: (2026)
Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies
by: Wang, Junlin, et al.
Published: (2024)
by: Wang, Junlin, et al.
Published: (2024)
Compressed Context Memory For Online Language Model Interaction
by: Kim, Jang-Hyun, et al.
Published: (2023)
by: Kim, Jang-Hyun, et al.
Published: (2023)
Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models
by: Puerto, Haritz, et al.
Published: (2024)
by: Puerto, Haritz, et al.
Published: (2024)
Similar Items
-
What Defines Good Reasoning in LLMs? Dissecting Reasoning Steps with Multi-Aspect Evaluation
by: Do, Heejin, et al.
Published: (2025) -
Token Bottleneck: One Token to Remember Dynamics
by: Kim, Taekyung, et al.
Published: (2025) -
Rotary Position Embedding for Vision Transformer
by: Heo, Byeongho, et al.
Published: (2024) -
Masking meets Supervision: A Strong Learning Alliance
by: Heo, Byeongho, et al.
Published: (2023) -
RL makes MLLMs see better than SFT
by: Song, Junha, et al.
Published: (2025)