12 accepted papers
Existing solutions for bundle recommendation (BR) have achieved remarkable effectiveness for predicting the user’s preference for prebuilt bundles. However, bundle-item (B-I) affiliation will vary dynamically in real scenarios. For ex ample, a bundle themed as ‘casual outfit’ may add ‘hat’ or re
Large Language Model (LLM)-based Multi-Agent Systems (MAS) have become a popular paradigm of AI applications. However, trustworthiness issues in MAS remain a critical concern. Unlike challenges in single-agent systems, MAS involve more complex communication processes, making them susceptible to corr…
Source counting (SC) in an indoor environment is an important problem in computational auditory scene analysis. However, the problem is challenging, especially when reverberation and ambient noise are present in the environment. To address this problem, we propose an augmented Bayesian non-parametri…
Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing broad aspects of daily life. Despite their remarkable performance, LLMs exhibit a fundamental limitation: hallucination—the tendency to produce misleading outputs that appear plausible. This inherent…
Artificial intelligence (AI) has surpassed top human players in a variety of games. In imperfect information games, these achievements have primarily been driven by Counterfactual Regret Minimization (CFR) and its variants for computing Nash equilibrium. However, most existing research has focused o…
Since the rapid development of Large Language Models (LLMs) has achieved remarkable success, understanding and rectifying their internal complex mechanisms has become an urgent issue. Recent research has attempted to interpret their behaviors through the lens of inner representation. However, develo…
Acoustic signal processing in the circular harmonic domain (CHD) is an appealing method for speaker localization, since it inherently supports wideband acoustic sources and provides frequency invariant beampatterns. However, the performance of existing circular harmonic direction-of-arrival (DOA) es…
RGBT tracking has been widely used in various fields such as robotics, surveillance processing, and autonomous driving. Existing RGBT trackers fully explore the spatial information between the template and the search region and locate the target based on the appearance matching results. However, the…
Training with simulated data is a common approach in pose estimation research. However, a sim-to-real gap between clean simulated data and noisy real data will seriously weaken the generalization ability of the algorithm, especially for point clouds. To address this problem, this paper proposes a do…
Recurrent Neural Networks (RNNs) have demonstrated their effectiveness in learning and processing sequential data (e.g., speech and natural language). However, due to the black-box nature of neural networks, understanding the decision logic of RNNs is quite challenging. Some recent progress has been…
Estimating unknown background noise from single-channel noisy speech is a key yet challenging problem for speech enhancement. Given the fact that the background noises typically have the repeating property and the foreground speech is sparse and time-variant, many literatures decompose the noisy spe…
We consider the problem of decentralized detection of a hypothesis H using multiple sensors. The sensors also want to keep the fusion center from inferring about another hypothesis G. Each sensor makes an observation and summarizes the observation using a local decision rule. The sensor summaries ar…