Proposed Script-Normalized WER (SN-WER), reducing script mismatch inflation by up to 12% across five Indic languages, enhancing multi-script ASR evaluation accuracy.

Priyaranjan Pattnayak

SimSD employs a plug-and-play masking strategy to enable token-level speculative decoding in diffusion LLMs, achieving up to 7.46× speedup while maintaining quality.

Junxia Cui, Haotian Ye, Runchu Tian et al.

SafeSteer employs localized on-policy distillation focusing on safety tokens, reducing reliance on large datasets and auxiliary reward models, achieving a superior safety-capability trade-off.

Hao Li, Jingkun An, Zijun Song et al.

Iteris employs an explore-plan-execute loop with multi-agent collaboration to generate numerical evidence and proof drafts, verified through expert review, advancing open problems in computational mathematics.

Leheng Chen, Zihao Liu, Wanyi He et al.

Introducing FWAV-Sim, a high-fidelity Unity-based simulation platform integrating quasi-steady blade-element aerodynamics, fractal turbulence, and realistic sensor models, enabling robust FWAV autonomous system development.

Haichuan Li, Tomi Westerlund

This paper introduces GP-RV-GOMEA, a hybrid model-based evolutionary algorithm that simultaneously optimizes symbolic expression structures and real-valued constants, achieving significant accuracy improvements.

Johannes Koch, Tanja Alderliesten, Peter A. N. Bosman

This paper systematically evaluates 9 neuron models and 3 spike encoding schemes in SNN-based network intrusion detection, revealing latency encoding as the most effective approach, achieving 92.11% accuracy.

Raj Patel, David Amebley, Taye Akinrele et al.

Single-layer phase encoder-decoder system achieves nonlinear function approximation via interference, with error below 10^-8, no nonlinear materials needed.

Yuntian Wang, Alexander Chen, Md Sadman Sakib Rahman et al.

Lumos-Nexus employs a two-stage training and UPFB to bridge frequencies, boosting video fidelity and reasoning-driven generation.

Jiazheng Xing, Hangjie Yuan, Lingling Cai et al.

Introduces SOCO benchmark with over 1 million keypoint pairs across 100 categories, revealing that vision foundation models encode strong semantics but poorly transfer correspondences across categories.

Olaf Dünkel, Basavaraj Sunagad, Haoran Wang et al.

C4G introduces timestamp-conditioned learnable Gaussian tokens with transformer decoding, enabling efficient 4D scene reconstruction from monocular video without scene-specific optimization, reducing Gaussian count by orders of magnitude.

Mungyeom Kim, Minkyeong Jeon, Honggyu An et al.

LongTraceRL enhances long-context reasoning by generating complex multi-hop questions via knowledge graph random walks, using search trajectories for layered distractors, and entity-level rubric rewards, achieving significant improvements.

Nianyi Lin, Jiajie Zhang, Lei Hou et al.

Introduces context-dependent argumentation frameworks (CDAFs) with perspective activation, analyzing the complexity of strategic attack manipulation, establishing NP-completeness bounds.

Albert Sadowski, Jarosław A. Chudziak

This paper introduces the 'Disagreeing Rationales' framework, systematically analyzing how diverse human annotations and explanations impact hate speech detection, emphasizing the benefits of soft labels and rationales.

Benedetta Muscato, Beiduo Chen, Gizem Gezici et al.

This paper introduces TxFM, a masked autoencoder trained on 1.4 million RNA-seq samples, outperforming large-scale foundation models in gene representation learning.

Kian Kenyon-Dean, Alina Selega, Ihab Bendidi et al.

Proposes Functional Attention, transforming pointwise attention into linear operators in function spaces, achieving resolution-invariant PDE solving and 3D segmentation with superior performance.

Jiefang Xiao, Maolin Gao, Simon Weber et al.

Pure tactile-based deep RL enables multi-finger robot to control small object separation with success rates close to 94%, validated in real-world transfer.

Ulf Kasolowsky, Berthold Bäuml

IDOL employs inverse dynamics to decode future scene transitions into motion features, significantly improving autonomous driving trajectory planning.

Chenghao Zhang, Timin Li, Dongmei Li

REIS combines lightweight scene gating and KV-guided inference, significantly reducing robotic reasoning redundancy for real-time decision-making.

Joonhee Lee, Hyunseung Shin, Hyunmi Kim et al.

Proposes an adaptive control framework combining artificial time delay estimation with barrier Lyapunov functions for Euler-Lagrange robots, effectively handling state-dependent uncertainties and time-varying constraints.

Saksham Gupta, Rishabh Dev Yadav, Sarthak Mishra et al.