18 accepted papers
Large language models (LLMs) have revolutionized research in software engineering, and among various tasks, LLM-based code synthesis is promising. A recent line of benchmarks aims to evaluate LLM-generated codes in time efficiency, beyond their correctness. However, *space*, another vital aspect of …
*Model merging* offers an appealing route to multi-task learning by composing independently fine-tuned checkpoints without centralized data or retraining. However, this convenience can come with a hidden cost. Model merging may *amplify* performance disparities across subgroups, raising fairness con…
Soft robots are inherently compliant and safe, making them suitable for humaninteractive applications such as surgery. However, their nonlinear and hysteretic behavior poses significant challenges for accurate modeling and control. We present a soft robotic system and propose a hysteresis-aware whol…
Competitive programming is increasingly being used to evaluate the algorithmic reasoning capabilities of large language models (LLMs). However, existing benchmarks primarily focus on full-information tasks where all problem inputs are provided upfront. This overlooks a critical dimension of algorith…
With the widespread adoption of open-source code language models (code LMs), intellectual property (IP) protection has become an increasingly critical concern. While current watermarking techniques have the potential to identify the code LM to protect its IP, they have limitations when facing the mo
Representing and synthesizing novel views in real-world dynamic scenes from casual monocular videos is a long-standing problem. Existing solutions typically approach dynamic scenes by applying geometry techniques or utilizing temporal information between several adjacent frames without considering t…
We explore the potential of \emph{AI-enhanced combinatorial optimization theory}, taking online bipartite matching (OBM) as a case study. In the theoretical study of OBM, the \emph{hardness} corresponds to a performance \emph{upper bound} of a specific online algorithm or any possible online algorit…
Soft robots are inherently compliant and safe, making them suitable for human-interactive applications such as surgery. However, their nonlinear and hysteretic behavior, arising from the properties of soft materials, presents substantial challenges for accurate modeling and control. In this study, w
Network quantization, one of the most widely studied model compression methods, effectively quantizes a floating-point model to obtain a fixed-point one with negligible accuracy loss. Although great success was achieved in reducing the model size, it may exacerbate the unfairness in model accuracy…
Generating high-quality, realistic rendering images for real-time applications generally requires tracing a few samples-per-pixel (spp) and using deep learning-based approaches to denoise the resulting low-spp images. Existing denoising methods necessitate a substantial time expenditure when renderi…
For a specific online optimization problem, for example, online bipartite matching (OBM), research efforts could be made in two directions before it is finally closed, i.e., the optimal competitive online algorithm is found. One is to continuously design algorithms with better performance. To this e…
After large models (LMs) have gained widespread acceptance in code-related tasks, their superior generative capacity has greatly promoted the application of the code LM. Nevertheless, the security of the generated code has raised attention to its potential damage. Existing secure code generation met…
Safe human-robot interaction and excellent motion flexibility ensure a wide range of potential applications for soft robots in industry and medicine. Although many efforts have been made to empower soft robots with variable stiffness, solutions for miniaturization, wide-range, and rapid-response sti
To handle a large amount of unlabeled data, batch active learning (BAL) queries humans for the labels of a batch of the most valuable data points at every round. Most current BAL strategies are based on human-designed heuristics, such as uncertainty sampling or mutual information maximization. Howev…
Chinese Spelling Correction (CSC) is a task to detect and correct misspelled characters in Chinese texts. CSC is challenging since many Chinese characters are visually or phonologically similar but with quite different semantic meanings. Many recent works use BERT-based language models to directly c…
The flexible manipulators and related robotic systems have been widely used in minimally invasive surgery (MIS) for enhancing the intraoperative inspection and surgical operation. Although a variety of flexible manipulators using different mechanisms have been developed, most of them are rigid mecha
Deep learning architectures with a huge number of parameters are often compressed using
Soft robotic technologies offer a promising solution for unconstructed applications due to their complete softness, robustness, and flexibility. In this letter, we explore the design and modularization of the flexible pneumatic robotic actuators for applying in minimally invasive surgery or other co