arXiv:2602.22555v2 Announce Type: replace-cross Abstract: Electroencephalogram (EEG) signals have become a popular medium for decoding visual information due to their cost-effectiveness and high temporal resolution. However, current approaches face significant challenges in bridging the modality gap between EEG and image data. These methods typically rely on complex adaptation processes involving multiple stages, making it hard […]
Is continuous CoT better suited for multi-lingual reasoning?
arXiv:2603.08177v1 Announce Type: cross Abstract: We investigate whether performing reasoning in a continuous latent space leads to more robust multilingual capabilities. We compare Continuous Chain-of-Thought (using the CODI framework) against standard supervised fine-tuning across five typologically diverse languages: English, Chinese, German, French, and Urdu. Our experiments on GSM8k and CommonsenseQA demonstrate that continuous reasoning significantly […]
A Recipe for Stable Offline Multi-agent Reinforcement Learning
arXiv:2603.08399v1 Announce Type: cross Abstract: Despite remarkable achievements in single-agent offline reinforcement learning (RL), multi-agent RL (MARL) has struggled to adopt this paradigm, largely persisting with on-policy training and self-play from scratch. One reason for this gap comes from the instability of non-linear value decomposition, leading prior works to avoid complex mixing networks in favor […]
Beyond Hungarian: Match-Free Supervision for End-to-End Object Detection
arXiv:2603.08514v1 Announce Type: cross Abstract: Recent DEtection TRansformer (DETR) based frameworks have achieved remarkable success in end-to-end object detection. However, the reliance on the Hungarian algorithm for bipartite matching between queries and ground truths introduces computational overhead and complicates the training dynamics. In this paper, we propose a novel matching-free training scheme for DETR-based detectors […]
UNISEP: A Unified Sensor Placement Framework for Human Motion Capture and Wearables
arXiv:2412.21159v2 Announce Type: replace Abstract: The proliferation of wearable sensors and monitoring technologies has created a need for standardized sensor placement protocols. While existing standards like the Surface Electromyography for Non-Invasive Assessment of Muscles (SENIAM) recommendations for electromyography (EMG) and the 10-20 system for electroencephalography (EEG) address modality-specific applications, no comprehensive framework spans different sensing […]
Fast reconstruction of degenerate populations of conductance-based neuron models from spike times
arXiv:2509.12783v2 Announce Type: replace Abstract: Inferring the biophysical parameters of conductance-based models (CBMs) from experimentally accessible recordings remains a central challenge in computational neuroscience. Spike times are the most widely available data, yet they reveal little about which combinations of ion channel conductances generate the observed activity. This inverse problem is further complicated by neuronal […]
RadDiff: Retrieval-Augmented Denoising Diffusion for Protein Inverse Folding
arXiv:2512.00126v2 Announce Type: replace Abstract: Protein inverse folding, the design of an amino acid sequence based on a target protein structure, is a fundamental problem of computational protein engineering. Existing methods either generate sequences without leveraging external knowledge or relying on protein language models~(PLMs). The former omits the knowledge stored in natural protein data, while […]
NAAMSE: Framework for Evolutionary Security Evaluation of Agents
arXiv:2602.07391v2 Announce Type: replace Abstract: AI agents are increasingly deployed in production, yet their security evaluations remain bottlenecked by manual red-teaming or static benchmarks that fail to model adaptive, multi-turn adversaries. We propose NAAMSE, an evolutionary framework that reframes agent security evaluation as a feedback-driven optimization problem. Our system employs a single autonomous agent that […]
Bounds on $R_0$ and final epidemic size when the next-generation matrix $M$ is only partially known
arXiv:2602.23885v2 Announce Type: replace Abstract: We study a multitype SIR epidemic model where individuals are categorized into different types, and where infection spread is characterized by a next-generation matrix $M=m_ij$ with community fractions $\pi_j$ for the different types of individuals. We analyse two key quantities: the basic reproduction number $R_0$ and the final epidemic outcome […]
Expectation-maximization for structure determination directly from cryo-EM micrographs
arXiv:2303.02157v3 Announce Type: replace-cross Abstract: A single-particle cryo-electron microscopy (cryo-EM) measurement, called a micrograph, consists of multiple two-dimensional tomographic projections of a three-dimensional (3-D) molecular structure at unknown locations, taken under unknown viewing directions. All existing cryo-EM algorithmic pipelines first locate and extract the projection images, and then reconstruct the structure from the extracted images. […]
Puppet-CNN: Continuous Parameter Dynamics for Input-Adaptive Convolutional Networks
arXiv:2411.12876v2 Announce Type: replace-cross Abstract: Modern convolutional neural networks (CNNs) organize computation as a discrete stack of layers whose parameters are independently stored and learned, with the number of layers fixed as an architectural hyperparameter. In this work, we explore an alternative perspective: can network parameterization itself be modeled as a continuous dynamical system? We […]
ViLAM: Distilling Vision-Language Reasoning into Attention Maps for Social Robot Navigation
arXiv:2503.09820v2 Announce Type: replace-cross Abstract: We introduce ViLAM, a novel method for distilling vision-language reasoning from large Vision-Language Models (VLMs) into spatial attention maps for socially compliant robot navigation. Unlike traditional methods that rely on expert demonstrations or human-annotated datasets, ViLAM performs knowledge distillation and fine-tuning at the intermediate layer representation (attention) level by aligning […]