Search Results for author:
Found 9 papers, 7 papers with code
Training-Free Long-Context Scaling of Large Language Models
The ability of Large Language Models (LLMs) to process and generate coherent text is markedly weakened when the number of input tokens exceeds their pretraining length.
BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models
Multimodal reasoning stands as a pivotal capability for large vision-language models (LVLMs).
Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models
This work explores the integration of diffusion models and Chain-of-Thought (CoT), a well-established technique to improve the reasoning ability in autoregressive language models.
DiffuSeq-v2: Bridging Discrete and Continuous Text Spaces for Accelerated Seq2Seq Diffusion Models
Diffusion models have gained prominence in generating high-quality sequences of text.
L-Eval: Instituting Standardized Evaluation for Long Context Language Models
Recently, there has been growing interest in extending the context length of large language models (LLMs), aiming to effectively process long inputs of one turn or conversations with more extensive histories.
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Bringing together theoretical analysis and empirical evidence, we demonstrate the great potential of diffusion models in complex conditional language generation tasks.
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration
Natural Language Inference Generation task is to generate a text hypothesis given a text premise and a logical relation between the two.
Positive, Negative and Neutral: Modeling Implicit Feedback in Session-based News Recommendation
News recommendation for anonymous readers is a useful but challenging task for many news portals, where interactions between readers and articles are limited within a temporary login session.
