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Found 9 papers, 5 papers with code
Improving Controllable Text Generation with Position-Aware Weighted Decoding
Weighted decoding methods composed of the pretrained language model (LM) and the controller have achieved promising results for controllable text generation.
Learning Fine-Grained Grounded Citations for Attributed Large Language Models
Despite the impressive performance on information-seeking tasks, large language models (LLMs) still struggle with hallucinations.
Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
To mitigate this, we further propose a training-free method called Residual Visual Decoding, where we revise the output distribution of LVLMs with the one derived from the residual visual input, providing models with direct access to the visual information.
An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation
Retrieval-augmented generation integrates the capabilities of large language models with relevant information retrieved from an extensive corpus, yet encounters challenges when confronted with real-world noisy data.
Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement
In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement against varying scenarios. Specifically, we embed a pre-trained generator to Retinex model to produce reflectance maps with enhanced detail and vividness, thereby recovering features degraded by low-light conditions. Taking one step further, we introduce a novel optimization strategy, which backpropagates the gradients to the input seeds rather than the parameters of the low-light enhancement model, thus intactly retaining the generative knowledge learned from natural images and achieving faster convergence speed.
Controllable Text Generation via Probability Density Estimation in the Latent Space
Previous work on controllable text generation has explored the idea of control from the latent space, such as optimizing a representation with attribute-related classifiers or sampling a representation from relevant discrete samples.
Electrochemical Parameter Identification for Lithium-ion Battery Sources in Self-Sustained Transportation Energy Systems
Based on the sensitivity indexes, the SSO algorithm can decouple the mixed impacts of different parameters during the identification.
A simplified electro-chemical lithium-ion battery model applicable for in situ monitoring and online control
The penetrations of lithium-ion batteries in transport, energy and communication systems are increasing rapidly.
