#Model Efficiency
Latest news articles tagged with "Model Efficiency". Follow the timeline of events, related topics, and entities.
Articles (9)
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🇺🇸 The Master Key Hypothesis: Unlocking Cross-Model Capability Transfer via Linear Subspace Alignment
[USA]
arXiv:2604.06377v1 Announce Type: cross Abstract: We investigate whether post-trained capabilities can be transferred across models without retraining, with a focus on transfer across different model...
Related: #Artificial Intelligence, #Machine Learning -
🇺🇸 R2-Dreamer: Redundancy-Reduced World Models without Decoders or Augmentation
[USA]
arXiv:2603.18202v1 Announce Type: cross Abstract: A central challenge in image-based Model-Based Reinforcement Learning (MBRL) is to learn representations that distill essential information from irre...
Related: #AI Research -
🇺🇸 MoLoRA: Composable Specialization via Per-Token Adapter Routing
[USA]
arXiv:2603.15965v1 Announce Type: cross Abstract: Multi-adapter serving systems route entire sequences to a single adapter, forcing a choice when requests span multiple domains. This assumption fails...
Related: #AI Specialization -
🇺🇸 FineRMoE: Dimension Expansion for Finer-Grained Expert with Its Upcycling Approach
[USA]
arXiv:2603.13364v1 Announce Type: cross Abstract: As revealed by the scaling law of fine-grained MoE, model performance ceases to be improved once the granularity of the intermediate dimension exceed...
Related: #AI Optimization -
🇺🇸 Efficiently Aligning Draft Models via Parameter- and Data-Efficient Adaptation
[USA]
arXiv:2603.09527v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference but suffers from performance degradation when target models are fine-tuned for specific domains. A nai...
Related: #AI Alignment -
🇺🇸 Grouter: Decoupling Routing from Representation for Accelerated MoE Training
[USA]
arXiv:2603.06626v1 Announce Type: cross Abstract: Traditional Mixture-of-Experts (MoE) training typically proceeds without any structural priors, effectively requiring the model to simultaneously tra...
Related: #AI Training -
🇺🇸 Ruyi2 Technical Report
[USA]
arXiv:2602.22543v1 Announce Type: cross Abstract: Large Language Models (LLMs) face significant challenges regarding deployment costs and latency, necessitating adaptive computing strategies. Buildin...
Related: #Adaptive Computing, #Distributed Training -
🇺🇸 Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward
[USA]
arXiv:2602.12430v1 Announce Type: cross Abstract: The transition from monolithic language models to modular, skill-equipped agents marks a defining shift in how large language models (LLMs) are deplo...
Related: #AI Architecture, #Knowledge Management -
🇺🇸 Steering Large Reasoning Models towards Concise Reasoning via Flow Matching
[USA]
arXiv:2602.05539v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) excel at complex reasoning tasks, but their efficiency is often hampered by overly verbose outputs. Prior steering meth...
Related: #Artificial Intelligence, #Machine Learning
Key Entities (3)
- Mixture of experts (2 news)
- Large language model (2 news)
- Unlock (charity) (1 news)
About the topic: Model Efficiency
The topic "Model Efficiency" aggregates 9+ news articles from various countries.