:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Du, Yupei, Song, Yingjin, Wong, Hugh Mee, Ignatev, Daniil, Gatt, Albert, Nguyen, Dong
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Machine Learning
Online Access:	https://arxiv.org/abs/2507.03648
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
by: Du, Yupei, et al.
Published: (2023)

DeMeVa at LeWiDi-2025: Modeling Perspectives with In-Context Learning and Label Distribution Learning
by: Ignatev, Daniil, et al.
Published: (2025)

Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?
by: Song, Yingjin, et al.
Published: (2025)

VAQUUM: Are Vague Quantifiers Grounded in Visual Data?
by: Wong, Hugh Mee, et al.
Published: (2025)

Don't Learn, Ground: A Case for Natural Language Inference with Visual Grounding
by: Ignatev, Daniil, et al.
Published: (2025)

When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question-Answering
by: Wong, Hugh Mee, et al.
Published: (2026)

From Image Captioning to Visual Storytelling
by: Passadakis, Admitos, et al.
Published: (2025)

Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning
by: Song, Yingjin, et al.
Published: (2024)

Structured Pruning for Diverse Best-of-N Reasoning Optimization
by: Nguyen, Hieu Trung, et al.
Published: (2025)

Demystifying When Pruning Works via Representation Hierarchies
by: He, Shwai, et al.
Published: (2026)

Reason to Rote: Rethinking Memorization in Reasoning
by: Du, Yupei, et al.
Published: (2025)

You Do Not Fully Utilize Transformer's Representation Capacity
by: Gerasimov, Gleb, et al.
Published: (2025)

Adaptive Layer Selection for Layer-Wise Token Pruning in LLM Inference
by: Taniguchi, Rei, et al.
Published: (2026)

Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI
by: Man, Hieu, et al.
Published: (2026)

Disentangling Language Roles in Multilingual LLM Task Execution
by: Zhan, Qishi, et al.
Published: (2026)

Bypass Back-propagation: Optimization-based Structural Pruning for Large Language Models via Policy Gradient
by: Gao, Yuan, et al.
Published: (2024)

InnerThoughts: Disentangling Representations and Predictions in Large Language Models
by: Chételat, Didier, et al.
Published: (2025)

RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations
by: Huang, Jing, et al.
Published: (2024)

Dissecting Language Models: Machine Unlearning via Selective Pruning
by: Pochinkov, Nicholas, et al.
Published: (2024)

Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
by: Laptev, Daniil, et al.
Published: (2025)

Disentangled Representation Learning with Large Language Models for Text-Attributed Graphs
by: Qin, Yijian, et al.
Published: (2023)

Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
by: Hua, Wenyue, et al.
Published: (2024)

Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning
by: Schaffelder, Max, et al.
Published: (2025)

Kronecker Factorization Improves Efficiency and Interpretability of Sparse Autoencoders
by: Kurochkin, Vadim, et al.
Published: (2025)

Hypernetworks for Perspectivist Adaptation
by: Ignatev, Daniil, et al.
Published: (2025)

On the Ability of Transformers to Verify Plans
by: Sarrof, Yash, et al.
Published: (2026)

Quantifying Modality Contributions via Disentangling Multimodal Representations
by: Amit, Padegal, et al.
Published: (2025)

Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning
by: Shu, Dong, et al.
Published: (2024)

IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining
by: Li, Yixiao, et al.
Published: (2025)

PAT: Pruning-Aware Tuning for Large Language Models
by: Liu, Yijiang, et al.
Published: (2024)

Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning
by: Bi, Jiaxi, et al.
Published: (2026)

Large Language Model Pruning
by: Huang, Hanjuan, et al.
Published: (2024)

Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
by: Dong, Zican, et al.
Published: (2025)

Frustratingly Easy Task-aware Pruning for Large Language Models
by: Tian, Yuanhe, et al.
Published: (2025)

Interpretable Discriminative Text Representations via Agreement and Label Disentanglement
by: Wang, Tong, et al.
Published: (2026)

UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
by: Zhao, Yang, et al.
Published: (2025)

Is Random Attention Sufficient for Sequence Modeling? Disentangling Trainable Components in the Transformer
by: Dong, Yihe, et al.
Published: (2025)

Self-Data Distillation for Recovering Quality in Pruned Large Language Models
by: Thangarasa, Vithursan, et al.
Published: (2024)

Language Model-Driven Data Pruning Enables Efficient Active Learning
by: Azeemi, Abdul Hameed, et al.
Published: (2024)

Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
by: Ankner, Zachary, et al.
Published: (2024)