Hugging Face Trending Papers
Copy-Paste Language Models
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arXiv Computation and Language
Oct 15
Copy-Paste Language Models
arXiv:2610.19247v1 Announce Type: new Abstract: Transformers are intuitively considered to be efficient at copying from their inputs. We actually show that the ability of LLMs to copy in context can...
arXiv AI
Jun 10
PromptEmbedder: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting
arXiv:2605. 28066v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable efficacy in text embedding, yet current adaptation methods like LoRA face significant bottlenecks in computational efficiency and cross-architecture transferability.
arXiv Computation and Language
Oct 15
Titan-Llama: Retrofitting Pre-trained LLMs with External Neural Memory Modules
arXiv:2610.19210v1 Announce Type: new Abstract: Transformers are efficient to pre-train at scale because attention permits parallel computation across sequence positions, but long-context inference r...
arXiv AI
Sep 24
Scaling Attention Head Analysis via Gradient-Based Attribution in Context-Aware Machine Translation
arXiv:2609.28117v1 Announce Type: cross Abstract: In this paper, we introduce a gradient-based head attribution strategy where the Token-level Max-Margin loss is backpropagated to the attention maps....
arXiv Machine Learning
21h ago
An Information Bottleneck for Post-hoc Memorization Mitigation in LLMs
arXiv:2611.07669v1 Announce Type: new Abstract: Recent studies have shown that large language models (LLMs) can memorize and reproduce copyrighted training data, raising serious privacy and intellect...
arXiv AI
Jul 14
Extending LLM Context via Associative Recurrent Memory
arXiv:2607. 11614v1 Announce Type: cross Abstract: Extending the context length of large language models (LLMs) is critical for many real-world applications, yet standard transformers remain constrained by quadratic compute and linear memory scaling.