An Effective Framework to Help Large Language Models Handle Numeric-involved Long-context Tasks
Fuente:
arXiv
Guardado en:
| Autor principal: | Yu, Yijiong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Patience Is The Key to Large Language Model Reasoning
por: Yu, Yijiong
Publicado: (2024)
por: Yu, Yijiong
Publicado: (2024)
Long-context Language Models Fail in Basic Retrieval Tasks Without Sufficient Reasoning Steps
por: Yu, Yijiong, et al.
Publicado: (2024)
por: Yu, Yijiong, et al.
Publicado: (2024)
Training With "Paraphrasing the Original Text" Teaches LLM to Better Retrieve in Long-context Tasks
por: Yu, Yijiong, et al.
Publicado: (2023)
por: Yu, Yijiong, et al.
Publicado: (2023)
Accelerate Parallelizable Reasoning via Parallel Decoding within One Sequence
por: Yu, Yijiong
Publicado: (2025)
por: Yu, Yijiong
Publicado: (2025)
Do LLMs Really Think Step-by-step In Implicit Reasoning?
por: Yu, Yijiong
Publicado: (2024)
por: Yu, Yijiong
Publicado: (2024)
Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models
por: Wu, Junjie, et al.
Publicado: (2025)
por: Wu, Junjie, et al.
Publicado: (2025)
Large Language Models Can Self-Improve in Long-context Reasoning
por: Li, Siheng, et al.
Publicado: (2024)
por: Li, Siheng, et al.
Publicado: (2024)
LongReward: Improving Long-context Large Language Models with AI Feedback
por: Zhang, Jiajie, et al.
Publicado: (2024)
por: Zhang, Jiajie, et al.
Publicado: (2024)
SWAA: Sliding Window Attention Adaptation for Efficient and Quality Preserving Long Context Processing
por: Yu, Yijiong, et al.
Publicado: (2025)
por: Yu, Yijiong, et al.
Publicado: (2025)
Large Language Models are In-context Teachers for Knowledge Reasoning
por: Zhao, Jiachen, et al.
Publicado: (2023)
por: Zhao, Jiachen, et al.
Publicado: (2023)
Diversity Helps Jailbreak Large Language Models
por: Zhao, Weiliang, et al.
Publicado: (2024)
por: Zhao, Weiliang, et al.
Publicado: (2024)
Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models
por: Qiu, Yifu, et al.
Publicado: (2025)
por: Qiu, Yifu, et al.
Publicado: (2025)
Investigating Numerical Translation with Large Language Models
por: Tang, Wei, et al.
Publicado: (2025)
por: Tang, Wei, et al.
Publicado: (2025)
How do Large Language Models Handle Multilingualism?
por: Zhao, Yiran, et al.
Publicado: (2024)
por: Zhao, Yiran, et al.
Publicado: (2024)
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
por: Zhang, Yusen, et al.
Publicado: (2024)
por: Zhang, Yusen, et al.
Publicado: (2024)
Evaluating the Effectiveness of Cost-Efficient Large Language Models in Benchmark Biomedical Tasks
por: Jahan, Israt, et al.
Publicado: (2025)
por: Jahan, Israt, et al.
Publicado: (2025)
Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs
por: Arnaiz-Rodriguez, Adrian, et al.
Publicado: (2025)
por: Arnaiz-Rodriguez, Adrian, et al.
Publicado: (2025)
When Long Helps Short: How Context Length in Supervised Fine-tuning Affects Behavior of Large Language Models
por: Zheng, Yingming, et al.
Publicado: (2025)
por: Zheng, Yingming, et al.
Publicado: (2025)
Structured In-context Environment Scaling for Large Language Model Reasoning
por: Yu, Peng, et al.
Publicado: (2025)
por: Yu, Peng, et al.
Publicado: (2025)
How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models
por: Jiang, Jiyue, et al.
Publicado: (2024)
por: Jiang, Jiyue, et al.
Publicado: (2024)
Mitigate Position Bias in Large Language Models via Scaling a Single Dimension
por: Yu, Yijiong, et al.
Publicado: (2024)
por: Yu, Yijiong, et al.
Publicado: (2024)
Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks
por: Chatterjee, Anwoy, et al.
Publicado: (2024)
por: Chatterjee, Anwoy, et al.
Publicado: (2024)
ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage
por: Lee, Taewhoo, et al.
Publicado: (2024)
por: Lee, Taewhoo, et al.
Publicado: (2024)
CDT: A Comprehensive Capability Framework for Large Language Models Across Cognition, Domain, and Task
por: Mo, Haosi, et al.
Publicado: (2025)
por: Mo, Haosi, et al.
Publicado: (2025)
Aligning Language Models to Explicitly Handle Ambiguity
por: Kim, Hyuhng Joon, et al.
Publicado: (2024)
por: Kim, Hyuhng Joon, et al.
Publicado: (2024)
What is Wrong with Perplexity for Long-context Language Modeling?
por: Fang, Lizhe, et al.
Publicado: (2024)
por: Fang, Lizhe, et al.
Publicado: (2024)
Mis-prompt: Benchmarking Large Language Models for Proactive Error Handling
por: Zeng, Jiayi, et al.
Publicado: (2025)
por: Zeng, Jiayi, et al.
Publicado: (2025)
Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
por: Ji, Yuelyu, et al.
Publicado: (2024)
por: Ji, Yuelyu, et al.
Publicado: (2024)
Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Model
por: Gao, Chaochen, et al.
Publicado: (2024)
por: Gao, Chaochen, et al.
Publicado: (2024)
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task
por: Liu, Wenhan, et al.
Publicado: (2024)
por: Liu, Wenhan, et al.
Publicado: (2024)
MidPO: Dual Preference Optimization for Safety and Helpfulness in Large Language Models via a Mixture of Experts Framework
por: Qi, Yupeng, et al.
Publicado: (2025)
por: Qi, Yupeng, et al.
Publicado: (2025)
FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding
por: Deng, Jingyang, et al.
Publicado: (2024)
por: Deng, Jingyang, et al.
Publicado: (2024)
Can Large Language Models Handle Discourse Particles? A Case Study of Colloquial Malay
por: Yusoff, Mariah Al Giptiah Binte, et al.
Publicado: (2026)
por: Yusoff, Mariah Al Giptiah Binte, et al.
Publicado: (2026)
Density-aware Soft Context Compression with Semi-Dynamic Compression Ratio
por: Yu, Yijiong, et al.
Publicado: (2026)
por: Yu, Yijiong, et al.
Publicado: (2026)
Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism
por: Yu, Yijiong, et al.
Publicado: (2026)
por: Yu, Yijiong, et al.
Publicado: (2026)
Diversity Enhances an LLM's Performance in RAG and Long-context Task
por: Wang, Zhichao, et al.
Publicado: (2025)
por: Wang, Zhichao, et al.
Publicado: (2025)
Learning to Seek Help: Dynamic Collaboration Between Small and Large Language Models
por: Zeng, Hang, et al.
Publicado: (2026)
por: Zeng, Hang, et al.
Publicado: (2026)
Uncertainty Unveiled: Can Exposure to More In-context Examples Mitigate Uncertainty for Large Language Models?
por: Wang, Yifei, et al.
Publicado: (2025)
por: Wang, Yifei, et al.
Publicado: (2025)
Can Reasoning Help Large Language Models Capture Human Annotator Disagreement?
por: Ni, Jingwei, et al.
Publicado: (2025)
por: Ni, Jingwei, et al.
Publicado: (2025)
Evaluating Computational Accuracy of Large Language Models in Numerical Reasoning Tasks for Healthcare Applications
por: Malghan, Arjun R.
Publicado: (2025)
por: Malghan, Arjun R.
Publicado: (2025)
Ejemplares similares
-
Patience Is The Key to Large Language Model Reasoning
por: Yu, Yijiong
Publicado: (2024) -
Long-context Language Models Fail in Basic Retrieval Tasks Without Sufficient Reasoning Steps
por: Yu, Yijiong, et al.
Publicado: (2024) -
Training With "Paraphrasing the Original Text" Teaches LLM to Better Retrieve in Long-context Tasks
por: Yu, Yijiong, et al.
Publicado: (2023) -
Accelerate Parallelizable Reasoning via Parallel Decoding within One Sequence
por: Yu, Yijiong
Publicado: (2025) -
Do LLMs Really Think Step-by-step In Implicit Reasoning?
por: Yu, Yijiong
Publicado: (2024)