11 accepted papers
Multi-task learning often suffers from gradient conflicts, leading to unfair optimization and degraded overall performance. To address this, we present SVFair, a Shapley value-based framework for fair gradient aggregation. We propose two scalable geometric conflict metrics: VolDet, a gram determinan…
Detecting fraudulent online text is essential, as these manipulative messages exploit human greed, deceive individuals, and endanger societal security. Currently, this task remains under-explored on the Chinese web due to the lack of a comprehensive dataset of Chinese fraudulent texts. However, crea…
Generative models, particularly diffusion model, have emerged as powerful tools for sequential recommendation. However, accurately modeling user preferences remains challenging due to the noise perturbations inherent in the forward and reverse processes of diffusion-based methods. Towards this end,
Supervised fine-tuning (SFT) is widely adopted for tailoring large language models (LLMs) to specific downstream tasks. However, the substantial computational demands of LLMs hinder iterative exploration of fine-tuning datasets and accurate evaluation of individual sample importance. To address this…
Although large language models (LLMs) trained on extensive multilingual corpora exhibit impressive language transfer, they often fail to respond in the user’s desired language due to corpus imbalances, an embarrassingly simple problem known as the language confusion. However, existing solutions like…
Honest alignment refers to the ability of a language model to truthfully convey its knowledge limitations by appropriately refusing to answer questions when it lacks sufficient information. Existing solutions, such as prompt engineering and fine-tuning, face limitations: the former provides only mar…
Traditional interactive environments limit agents' intelligence growth with fixed tasks. Recently, single-agent environments address this by generating new tasks based on agent actions, enhancing task diversity. We consider the decision-making problem in multi-agent settings, where tasks are further…
Audio-visual speech enhancement (AV-SE) methods utilize auxiliary visual cues to enhance speakers’ voices. Therefore, technically they should be able to outperform the audio-only speech enhancement (SE) methods. However, there are few works in the literature on an AV-SE system that can work in real…
Recent researches reveal that StyleGAN can generate highly realistic images, inspiring researchers to use pretrained StyleGAN to generate high-fidelity swapped faces. However, existing methods fail to meet the expectations in two essential aspects of high-fidelity face swapping. Their results are bl…
Continuous speech separation using a microphone array was shown to be promising in dealing with the speech overlap problem in natural conversation transcription. This paper proposes VarArray, an array-geometry-agnostic speech separation neural network model. The proposed model is applicable to any n…
Image-based virtual try-on aims to synthesize the customer image with an in-shop clothes image to acquire seamless and natural try-on results, which have attracted increasing attentions. The main procedures of image-based virtual try-on usually consist of clothes image generation and try-on image sy…