25 accepted papers
In modern large language models (LLMs), LLM alignment is of crucial importance and is typically achieved through methods such as reinforcement learning from human feedback (RLHF) and direct preference optimization (DPO). However, in most existing methods for LLM alignment, all tokens in the response…
Current large language models (LLMs) generally show a significant performance gap in alignment between English and other languages.To bridge this gap, existing research typically leverages the model’s responses in English as a reference to select the best/worst responses in other languages, which ar
Continually expanding new languages for existing large language models (LLMs) is a promising yet challenging approach to building powerful multilingual LLMs.The biggest challenge is to make the model continuously learn new languages while preserving the proficient ability of old languages.To achieve…
Multilingual knowledge editing (MKE) aims to simultaneously update factual knowledge across multiple languages within large language models (LLMs). Previous research indicates that the same knowledge across different languages within LLMs exhibits a degree of shareability. However, most existing MKE…
4D millimeter-wave radar has gained attention as an emerging sensor for autonomous driving in recent years. However, existing 4D radar and camera fusion models often fail to fully exploit complementary information within each modality and lack deep cross-modal interactions. To address these issues,
Differential equations are widely used to describe complex dynamical systems with evolving parameters in nature and engineering. Effectively learning a family of maps from the parameter function to the system dynamics is of great significance. In this study, we propose a novel learning framework of…
"We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic understanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation. Accurately reconstructing such interactions in is c…
Precise and smooth control of an electromagnetic actuated micropositioner is a challenging task due to the system's nonlinear electromagnetic dynamics, as well as its unique structure and application scenarios. The main challenges include high-order nonlinearity, modeling uncertainties, input buffet
Knowledge distillation (KD) is known as a promising solution to compress large language models (LLMs) via transferring their knowledge to smaller models. During this process, white-box KD methods usually minimize the distance between the output distributions of the two models so that more knowledge…
Modeling complex systems using standard neural ordinary differential equations (NODEs) often faces some essential challenges, including high computational costs and susceptibility to local optima. To address these challenges, we propose a simulation-free framework, called Fourier NODEs (FNODEs), tha…
Graph-based multi-armed bandit algorithms utilize the relationship between users to select the best item to recommend for maximal reward, which is decided by items’ features and un-known users’ preferences. Therefore, the precise estimation of users’ preferences is fairly important and indispensable…
We revisit the well-studied image segmentation problem from a soft labeling perspective: instead of estimating integer labels per pixel indicating a finite set of classes, each pixel is assigned a real number that conveys the level of uncertainty in the estimated class label. Soft labels are useful,…
Existing syntactically-controlled paraphrase generation (SPG) models perform promisingly with human-annotated or well-chosen syntactic templates. However, the difficulty of obtaining such templates actually hinders the practical application of SPG models. For one thing, the prohibitive cost makes it…
In minimally invasive surgery (MIS), the field of view (FOV) plays a vital role. To enhance the stability of FOV and lighten the burden on surgeons, robot-assisted laparoscope systems have been developed and introduced into surgery. However, most of the existing automatic surgical tool tracking sche
Sampling of bandlimited (BL) graph signals is one fundamental problem in graph signal processing (GSP), whose underlying kernel is an irregular graph rather than regular 1-D time-series kernel in classical discrete signal processing (DSP). Though there were amounts of sampling objectives and algorit…
In image-guided robotic surgery, there exist different endoscopes coupled either with specialized surgical robots (SSRs) or general industrial robots (GIRs). In general, SSRs mechanically respect the remote-center-of-motion (RCM) constraints with directly and explicitly controllable degrees-of-freed
In minimally invasive surgery, endoscopes serve as the eyes of surgeon. To avoid fatigue in manual endoscope steering, robotic endoscope holders have been developed. Unfortunately, existing robotic endoscope holders are not widely adopted due to the poor surgeon-robot cooperation. In this work, we d
Generating adversarial examples for Neural Machine Translation (NMT) with single Round-Trip Translation (RTT) has achieved promising results by releasing the meaning-preserving restriction. However, a potential pitfall for this approach is that we cannot decide whether the generated examples are adv…
In this paper, we proposed an autonomous robotic flexible endoscope system for the laparoscopic bariatric surgery (LBS). This system comprises a UR5 robot and a flexible endoscope equipped with a novel continuum joint, named reinforced double helix continuum mechanism. Compared with the simple helix…
Colorectal cancer incidence has been steadily rising worldwide. Magnetic colonoscopes provide new approaches to conduct colon inspection and treatment. This paper presents a novel electromagnetically actuated soft-tethered colonoscope to achieve precise and stable orientation control. An inflated ba…
This letter presents a novel flexible robotic endoscope with a constrained tendon-driven continuum mechanism (CTCM) which is targeted for bariatric surgery. The robotic endoscope is composed of a UR5 robot and a CTCM-based flexible endoscope. By introducing a constraint tube, both the angulation and
High-definition 360 videos encoded in fine quality are typically too large in size to stream in its entirety over bandwidth (BW)-constrained networks. One popular remedy is to interactively extract and send a spatial sub-region corresponding to a viewer's current field-of-view (FoV) in a head-mounte…
Navigation through tubular environment is fundamental in tasks such as pipeline inspection, gastrointestinal tract inspection, etc. Conventional pipeline inspection robots are mostly made by rigid materials and could not well adapt to the large size variation of the environment. Soft robots provide…
This paper presents a novel magnetic anchored and steered camera robot intended for minimally invasive surgery (MIS), particularly for single port access (SPA) surgery. The design aims to achieve both compactness and a planar pan/tilt workspace (instead of hemispheric) to lower robot footprint in ve…
Acquisition device clustering from speech recordings is a new and critical problem in the field of speech forensic, which aims at merging speech recordings acquired by the same device into one cluster without both pre-knowing prior information of the processed data and pre-training classifier. We pr…