Papers
MMAU-Pro: A Challenging and Comprehensive Benchmark for Holistic Evaluation of Audio General Intelligence
Sonal Kumar, Šimon Sedláček, Vaibhavi Lokegaonkar et al.
Cliqueformer: Model-Based Optimization with Structured Transformers
Jakub Grudzien Kuba, Pieter Abbeel, Sergey Levine
Exploiting Missing Data Remediation Strategies Using Adversarial Missingness Attacks
Deniz Koyuncu, Alex Gittens, Bülent Yener et al.
Time Series Forecasting via Direct Per-Step Probability Distribution Modeling
Linghao Kong, Xiaopeng Hong
LatentLLM: Activation-Aware Transform to Multi-Head Latent Attention
Toshiaki Koike-Akino, Xiangyu Chen, Jing Liu et al.
On Logical Extrapolation for Mazes with Recurrent and Implicit Networks
Brandon Knutson, Amandin Chyba Rabeendran, Michael Ivanitskiy et al.
Object-Centric Latent Action Learning
Albina Klepach, Alexander Nikulin, Ilya Zisman et al.
Robust Detection of Synthetic Tabular Data Under Schema Variability
G. Charbel N. Kindji, Elisa Fromont, Lina M. Rojas-Barahona et al.
Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations
Yeongjong Kim, Namkyeong Cho, Minseok Kim et al.
Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption
Sunwoo Kim, Soo Yong Lee, Kyungho Kim et al.
A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm
Junhyung Lyle Kim, Nai-Hui Chia, Anastasios Kyrillidis
TabFlash: Efficient Table Understanding with Progressive Question Conditioning and Token Focusing
Jongha Kim, Minseong Bae, Sanghyeok Lee et al.
BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?
DoYoung Kim, Jin-Seop Lee, Noo-ri Kim et al.
Step-by-step Layered Design Generation
Faizan Farooq Khan, Joseph K J, Koustava Goswami et al.
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Loukas Kavouras, Eleni Psaroudaki, Konstantinos Tsopelas et al.
Detecting the Future: All-at-Once Event Sequence Forecasting with Horizon Matching
Ivan Karpukhin, Andrey Savchenko
HiCL: Hippocampal-Inspired Continual Learning
Kushal Kapoor, Wyatt Mackey, Yiannis Aloimonos et al.
GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation
Sungmin Kang, Jisoo Kim, Salman Avestimehr et al.
Understanding and Enhancing Differentiable Architecture Search from Information Bottleneck Perspective
Haidong Kang, Lianbo Ma, Pengjun Chen et al.
Sparse Additive Model Pruning for Order-Based Causal Structure Learning
Kentaro Kanamori, Hirofumi Suzuki, Takuya Takagi
Quantum Transformer for Molecular Learning: Multi-Configuration Ground-State Energy Prediction
Yuichi Kamata, Quoc Hoan Tran, Yasuhiro Endo et al.
HALO: Hardware-Aware Quantization with Low Critical-Path-Delay Weights for LLM Acceleration
Rohan Juneja, Shivam Aggarwal, Safeen Huda et al.