7 accepted papers
Multi-Hop Fact Verification (MHFV) necessitates complex reasoning across disparate evidence, posing significant challenges for Large Language Models (LLMs) which often suffer from hallucinations and fractured logical chains. Existing methods, while improving transparency via Chain-of-Thought (CoT), …
Few-shot keyword spotting aims to detect previously unseen keywords with very limited labeled samples. A pre-training and adaptation paradigm is typically adopted for this task. While effective in clean conditions, most existing approaches struggle with mixed keyword spotting--detecting multiple ove…
LiDAR-based 3D semantic segmentation is a critical task in autonomous driving, but its scalability is limited by the reliance on large-scale labeled datasets. Semi-supervised learning (SSL) offers a potential solution by leveraging unlabeled data. However, most existing SSL segmentation methods are …
Multi-sensor fusion is a key technology in the field of autonomous driving and robotics. Traditional offline multi-sensor fusion calibration methods rely on manual operations and fail to meet real-time requirements, while recent online calibration technologies have limited generalization capabilitie
Compared to large language models, traditional multimodal sentiment analysis frameworks are constrained by their classification heads, resulting in poor performance on zero-shot tasks. Moreover, due to limitations in visual encoders and multimodal fusion modules, most existing frameworks can only pr…
The end-to-end spoken language understanding system extracts the semantic intent directly from an input speech. It effectively avoids problems such as semantic drift in traditional cascade models. However, the lack of semantically labeled speech data makes the model training process diffi-cult. Seve…
Word segmentation task is the cornerstone of text processing. There are 7111 languages worldwide, most of which are low-resource languages. This paper attempts to solve the problem of multilingual unsupervised word segmentation using common points between languages without tagged corpus. We find tha…