Proposed DeepInsightTheorem framework enhances informal theorem proving by identifying core techniques, significantly outperforming baselines.

Yunhe Li, Hao Shi, Bowen Deng et al.

A dual-aspect evaluation framework analyzes LLMs on Vietnamese legal text, revealing readability-accuracy trade-offs.

Van-Truong Le

Proposed SAGR framework coordinates multi-robot language-guided search using semantic area graphs, improving efficiency by 18.8% in large environments.

Ruiyang Wang, Hao-Lun Hsu, Jiwoo Kim et al.

Task-reward optimization enhances Llama-3.2-3B-Instruct's performance on math datasets.

Sarthak Mittal, Leo Gagnon, Guillaume Lajoie

Using the CompCQ framework, this study analyzes LLM-generated competency questions across domains, revealing generation characteristics.

Reham Alharbi, Valentina Tamma, Terry R. Payne et al.

This study systematically evaluates various vision-language models for country-level image geolocalization, revealing their limitations in capturing fine-grained geographic cues.

Siddhant Bharadwaj, Ashish Vashist, Fahimul Aleem et al.

HILBERT framework achieves significant performance improvement in long-sequence audio-text representation learning through dual contrastive learning and information-balanced regularization.

Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin

Detect and suppress reward hacking using Gradient Fingerprints, achieving superior performance on math, code, and logical reasoning benchmarks.

Songtao Wang, Quang Hieu Pham, Fangcong Yin et al.

BAGEL benchmark evaluates language models' performance on animal knowledge using closed-book questions on taxonomy, morphology, etc.

Jiacheng Shen, Masato Hagiwara, Milad Alizadeh et al.

CollideNet enhances time-to-collision forecasting precision by disentangling temporal patterns in multi-scale video representation learning.

Nishq Poorav Desai, Ali Etemad, Michael Greenspan

Kometo algorithm achieves fast learning rates in multi-fidelity optimization without known smoothness or fidelity assumptions.

Come Fiegel, Victor Gabillon, Michal Valko

Proposed a two-stage deep learning framework using YOLOv8n and RexNet-150, achieving 95% accuracy in cheating detection.

Van-Truong Le, Le-Khanh Nguyen, Trong-Doanh Nguyen

DENALI dataset enables non-line-of-sight spatial reasoning with low-cost LiDARs, covering 72,000 scenes.

Nikhil Behari, Diego Rivero, Luke Apostolides et al.

Prototype-Grounded Concept Models (PGCMs) verify concept alignment via visual prototypes, enhancing interpretability.

Stefano Colamonaco, David Debot, Pietro Barbiero et al.

Combining convolution and delay learning in RSNNs achieves 52x inference speedup and 99% parameter savings on audio tasks.

Lúcio Folly Sanches Zebendo, Eleonora Cicciarella, Michele Rossi

SENSE leverages stereo vision and vision-language models to enhance open-vocabulary semantic segmentation, achieving a 2.9% precision improvement on PhraseStereo.

Thomas Campagnolo, Ezio Malis, Philippe Martinet et al.

Proposed a fleet sizing rule for multi-UAV missions ensuring 99.8% success, needing only four extra drones even under harshest conditions.

Vishal Ramesh, Antony Thomas

DTEA enables real-time switching between SEA and PEA topologies with switching time under 33.33 ms.

Vishal Ramesh, Aman Singh, Shishir Kolathaya

Proposed environment-adaptive solid-state LiDAR-inertial odometry, achieving 12.8% average RMSE reduction.

Zhi Zhang, Chalermchon Satirapod, Bingtao Ma et al.

In modular robots, Lamarckian evolution outperforms Darwinian in single-task optimization but declines under morphological diversity pressure.

Jed R Muff, Karine Miras, A. E. Eiben