:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Chao, Li, Bei, Zhang, Jiaqi, Liu, Xinyu, Fan, Yuchun, Lyu, Linkun, Chen, Xin, Wang, Jingang, Xiao, Tong, Pei, Peng, Cai, Xunliang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	https://arxiv.org/abs/2601.22580
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance
di: Fan, Yuchun, et al.
Pubblicazione: (2026)

Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning
di: Li, Bei, et al.
Pubblicazione: (2024)

Speculative Decoding via Early-exiting for Faster LLM Inference with Thompson Sampling Control Mechanism
di: Liu, Jiahao, et al.
Pubblicazione: (2024)

MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks
di: Ruan, Junhao, et al.
Pubblicazione: (2026)

Ltri-LLM: Streaming Long Context Inference for LLMs with Training-Free Dynamic Triangular Attention Pattern
di: Tang, Hongyin, et al.
Pubblicazione: (2024)

Scaling Embeddings Outperforms Scaling Experts in Language Models
di: Liu, Hong, et al.
Pubblicazione: (2026)

Causal Autoregressive Diffusion Language Model
di: Ruan, Junhao, et al.
Pubblicazione: (2026)

GradPower: Powering Gradients for Faster Language Model Pre-Training
di: Wang, Jinbo, et al.
Pubblicazione: (2025)

Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective
di: Shao, Ruichen, et al.
Pubblicazione: (2025)

ReMamba: Equip Mamba with Effective Long-Sequence Modeling
di: Yuan, Danlong, et al.
Pubblicazione: (2024)

Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection
di: Wang, Pei, et al.
Pubblicazione: (2024)

OneCAT: Decoder-Only Auto-Regressive Model for Unified Understanding and Generation
di: Li, Han, et al.
Pubblicazione: (2025)

FIRE: Flexible Integration of Data Quality Ratings for Effective Pre-Training
di: Xu, Liangyu, et al.
Pubblicazione: (2025)

Large-Scale Diverse Synthesis for Mid-Training
di: Zhang, Xuemiao, et al.
Pubblicazione: (2025)

Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs
di: Chen, Zhengyu, et al.
Pubblicazione: (2025)

Libra: Assessing and Improving Reward Model by Learning to Think
di: Zhou, Meng, et al.
Pubblicazione: (2025)

Scaling and Transferability of Annealing Strategies in Large Language Model Training
di: Wang, Siqi, et al.
Pubblicazione: (2025)

Dynamic Fisher-weighted Model Merging via Bayesian Optimization
di: Lee, Sanwoo, et al.
Pubblicazione: (2025)

BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search
di: Liu, Shiyu, et al.
Pubblicazione: (2026)

IIET: Efficient Numerical Transformer via Implicit Iterative Euler Method
di: Liu, Xinyu, et al.
Pubblicazione: (2025)

A Survey on LLM Mid-Training
di: Tu, Chengying, et al.
Pubblicazione: (2025)

What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation
di: Gong, Zhuocheng, et al.
Pubblicazione: (2024)

Aligning with Human Values to Enhance Interaction: An eHMI-Mediated Lane-Changing Negotiation Strategy Using Bayesian Inference
di: Peng, Boyao, et al.
Pubblicazione: (2025)

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces
di: Lyu, Yang, et al.
Pubblicazione: (2025)

APP: Adaptive Prototypical Pseudo-Labeling for Few-shot OOD Detection
di: Wang, Pei, et al.
Pubblicazione: (2023)

Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text
di: Xu, Zhihao, et al.
Pubblicazione: (2026)

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization
di: Bai, Yang, et al.
Pubblicazione: (2026)

Deep Learning based Quasi-consciousness Training for Robot Intelligent Model
di: Li, Yuchun, et al.
Pubblicazione: (2025)

Forgetting Curve: A Reliable Method for Evaluating Memorization Capability for Long-context Models
di: Liu, Xinyu, et al.
Pubblicazione: (2024)

SEAS: Self-Evolving Adversarial Safety Optimization for Large Language Models
di: Diao, Muxi, et al.
Pubblicazione: (2024)

LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points
di: Zhang, Xuemiao, et al.
Pubblicazione: (2025)

A Preliminary Study on the Promises and Challenges of Native Top-$k$ Sparse Attention
di: Xiu, Di, et al.
Pubblicazione: (2025)

NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables
di: Wang, Lanrui, et al.
Pubblicazione: (2025)

NDP: Next Distribution Prediction as a More Broad Target
di: Ruan, Junhao, et al.
Pubblicazione: (2024)

Rethinking the Sampling Criteria in Reinforcement Learning for LLM Reasoning: A Competence-Difficulty Alignment Perspective
di: Kong, Deyang, et al.
Pubblicazione: (2025)

Preference Curriculum: LLMs Should Always Be Pretrained on Their Preferred Data
di: Zhang, Xuemiao, et al.
Pubblicazione: (2025)

Parallel Decoding via Hidden Transfer for Lossless Large Language Model Acceleration
di: Wu, Pengfei, et al.
Pubblicazione: (2024)

FIRP: Faster LLM inference via future intermediate representation prediction
di: Wu, Pengfei, et al.
Pubblicazione: (2024)

FRAME: Boosting LLMs with A Four-Quadrant Multi-Stage Pretraining Strategy
di: Zhang, Xuemiao, et al.
Pubblicazione: (2025)

Expanding Reasoning Potential in Foundation Model by Learning Diverse Chains of Thought Patterns
di: Zhang, Xuemiao, et al.
Pubblicazione: (2025)