Saved in:
| Main Authors: | Jiang, Peijie, Feng, Yuqi, Peng, Cunyin, Zhao, Qian, Liu, Jia, Chen, KunLong, Zhang, Zhiqiang, Zhou, Jun |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.25704 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training
by: Tian, Changxin, et al.
Published: (2025)
by: Tian, Changxin, et al.
Published: (2025)
Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
by: Tian, Changxin, et al.
Published: (2025)
by: Tian, Changxin, et al.
Published: (2025)
RomanLens: The Role Of Latent Romanization In Multilinguality In LLMs
by: Saji, Alan, et al.
Published: (2025)
by: Saji, Alan, et al.
Published: (2025)
Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints
by: Peng, Songping, et al.
Published: (2026)
by: Peng, Songping, et al.
Published: (2026)
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
by: Xu, Wenjie, et al.
Published: (2023)
by: Xu, Wenjie, et al.
Published: (2023)
An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMs
by: Rai, Daking, et al.
Published: (2024)
by: Rai, Daking, et al.
Published: (2024)
CRISP: Persistent Concept Unlearning via Sparse Autoencoders
by: Ashuach, Tomer, et al.
Published: (2025)
by: Ashuach, Tomer, et al.
Published: (2025)
Benchmarking the Performance of Pre-trained LLMs across Urdu NLP Tasks
by: Tahir, Munief Hassan, et al.
Published: (2024)
by: Tahir, Munief Hassan, et al.
Published: (2024)
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
by: Luo, Yuqi, et al.
Published: (2024)
by: Luo, Yuqi, et al.
Published: (2024)
Training LLMs to Recognize Hedges in Spontaneous Narratives
by: Paige, Amie J., et al.
Published: (2024)
by: Paige, Amie J., et al.
Published: (2024)
Towards Effective and Efficient Continual Pre-training of Large Language Models
by: Chen, Jie, et al.
Published: (2024)
by: Chen, Jie, et al.
Published: (2024)
On Initializing Transformers with Pre-trained Embeddings
by: Kim, Ha Young, et al.
Published: (2024)
by: Kim, Ha Young, et al.
Published: (2024)
SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models
by: Liu, Han, et al.
Published: (2026)
by: Liu, Han, et al.
Published: (2026)
Text-Based Approaches to Item Difficulty Modeling in Large-Scale Assessments: A Systematic Review
by: Peters, Sydney, et al.
Published: (2025)
by: Peters, Sydney, et al.
Published: (2025)
Pre-trained Models Perform the Best When Token Distributions Follow Zipf's Law
by: He, Yanjin, et al.
Published: (2025)
by: He, Yanjin, et al.
Published: (2025)
EduGuardBench: A Holistic Benchmark for Evaluating the Pedagogical Fidelity and Adversarial Safety of LLMs as Simulated Teachers
by: Jiang, Yilin, et al.
Published: (2025)
by: Jiang, Yilin, et al.
Published: (2025)
LLMs and the Human Condition
by: Wallis, Peter
Published: (2024)
by: Wallis, Peter
Published: (2024)
Hardware Co-Design Scaling Laws via Roofline Modelling for On-Device LLMs
by: Sun, Luoyang, et al.
Published: (2026)
by: Sun, Luoyang, et al.
Published: (2026)
Learning Software Bug Reports: A Systematic Literature Review
by: Long, Guoming, et al.
Published: (2025)
by: Long, Guoming, et al.
Published: (2025)
Evaluating Relational Reasoning in LLMs with REL
by: Fesser, Lukas, et al.
Published: (2026)
by: Fesser, Lukas, et al.
Published: (2026)
Automatic Task Detection and Heterogeneous LLM Speculative Decoding
by: Ge, Danying, et al.
Published: (2025)
by: Ge, Danying, et al.
Published: (2025)
Pre-training data selection for biomedical domain adaptation using journal impact metrics
by: Laï-king, Mathieu, et al.
Published: (2024)
by: Laï-king, Mathieu, et al.
Published: (2024)
Breaking Free Transformer Models: Task-specific Context Attribution Promises Improved Generalizability Without Fine-tuning Pre-trained LLMs
by: Tytarenko, Stepan, et al.
Published: (2024)
by: Tytarenko, Stepan, et al.
Published: (2024)
Auditing Meta-Cognitive Hallucinations in Reasoning Large Language Models
by: Lu, Haolang, et al.
Published: (2025)
by: Lu, Haolang, et al.
Published: (2025)
Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs
by: Simhi, Adi, et al.
Published: (2024)
by: Simhi, Adi, et al.
Published: (2024)
Automated Bug Triaging using Instruction-Tuned Large Language Models
by: Kiashemshaki, Kiana, et al.
Published: (2025)
by: Kiashemshaki, Kiana, et al.
Published: (2025)
Toward Architecture-Aware Evaluation Metrics for LLM Agents
by: Souza, Débora, et al.
Published: (2026)
by: Souza, Débora, et al.
Published: (2026)
Merge-Bench: Resolve Merge Conflicts with Large Language Models
by: Schesch, Benedikt, et al.
Published: (2026)
by: Schesch, Benedikt, et al.
Published: (2026)
Universal Adversarial Attack on Aligned Multimodal LLMs
by: Rahmatullaev, Temurbek, et al.
Published: (2025)
by: Rahmatullaev, Temurbek, et al.
Published: (2025)
Improving LLMs with a knowledge from databases
by: Máša, Petr
Published: (2025)
by: Máša, Petr
Published: (2025)
The Unified Cognitive Consciousness Theory for Language Models: Anchoring Semantics, Thresholds of Activation, and Emergent Reasoning
by: Chang, Edward Y., et al.
Published: (2025)
by: Chang, Edward Y., et al.
Published: (2025)
ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning
by: Mi, Zhendong, et al.
Published: (2025)
by: Mi, Zhendong, et al.
Published: (2025)
An Industrial-Scale Insurance LLM Achieving Verifiable Domain Mastery and Hallucination Control without Competence Trade-offs
by: Zhu, Qian, et al.
Published: (2026)
by: Zhu, Qian, et al.
Published: (2026)
Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks
by: Kurian, Ashley, et al.
Published: (2025)
by: Kurian, Ashley, et al.
Published: (2025)
LLMs as Idiomatic Decompilers: Recovering High-Level Code from x86-64 Assembly for Dart
by: Abualazm, Raafat, et al.
Published: (2026)
by: Abualazm, Raafat, et al.
Published: (2026)
LLMs are Capable of Misaligned Behavior Under Explicit Prohibition and Surveillance
by: Ivanov, Igor
Published: (2025)
by: Ivanov, Igor
Published: (2025)
LLMs Are Not Scorers: Rethinking MT Evaluation with Generation-Based Methods
by: Cui, Hyang
Published: (2025)
by: Cui, Hyang
Published: (2025)
How LLMs Are Persuaded: A Few Attention Heads, Rerouted
by: Sun, Xiangkun, et al.
Published: (2026)
by: Sun, Xiangkun, et al.
Published: (2026)
RAG-Optimized Tibetan Tourism LLMs: Enhancing Accuracy and Personalization
by: Qi, Jinhu, et al.
Published: (2024)
by: Qi, Jinhu, et al.
Published: (2024)
Neither Valid nor Reliable? Investigating the Use of LLMs as Judges
by: Chehbouni, Khaoula, et al.
Published: (2025)
by: Chehbouni, Khaoula, et al.
Published: (2025)
Similar Items
-
WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training
by: Tian, Changxin, et al.
Published: (2025) -
Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
by: Tian, Changxin, et al.
Published: (2025) -
RomanLens: The Role Of Latent Romanization In Multilinguality In LLMs
by: Saji, Alan, et al.
Published: (2025) -
Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints
by: Peng, Songping, et al.
Published: (2026) -
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
by: Xu, Wenjie, et al.
Published: (2023)