POTATR is a lightweight 29M-parameter image-to-graph model that significantly improves page-level table extraction accuracy and efficiency.

Brandon Smock, Libin Liang, Max Sokolov et al.

Proposes an fully automated time-series forecasting framework combining high-frequency dataset TimeTrack with dynamic local telemetry, using NAS to generate accurate models, effectively addressing cold-start issues.

Abd Elghani Meliani, Arora Sagar, Adlen Ksentini et al.

Combines Quality Diversity (QD) algorithms with supervised discriminative models, using multi-frequency CPPNs and MAP-Elites to explore diverse audio solutions with high novelty and quality.

Björn Þór Jónsson, Çağrı Erdem, Stefano Fasciani et al.

Intervention-aware variational quantum predictive control (IA-VQC-DPC) significantly reduces safety violations and reliance on safety layers in building control, validated via safety attribution protocols.

Yifan Wang

DARP introduces difference-aware retrieval policies, leveraging local neighborhood structures to improve imitation learning robustness, achieving 15-46% performance gains over standard behavior cloning.

Quinn Pfeifer, Ethan Pronovost, Paarth Shah et al.

This paper reveals that RLHF achieves shallow alignment by compressing partisan signals without removing the underlying partisan structure, as shown through internal representation analysis of Llama 3.1 8B.

Wendy K. Tam

AdvGRPO framework combines dense multi-channel rewards and advantage decoupling for joint attacker-defender training, achieving over 90% attack success rate and superior defense robustness.

Blake Bullwinkel, Eugenia Kim, Amanda Minnich et al.

Proposes a logic-guided data extraction framework combining ASP and LLMs, reducing calls by 40% while maintaining accuracy.

Mario Alviano, Lorenzo Grillo, Nicola Leone et al.

Muon optimizer outperforms Adam in robustness and transferability, with larger logit margins and higher spectral rank in features.

Tianyu Ruan, Fengzhuo Zhang, Shuche Wang et al.

DexPIE improves dexterous manipulation policies using real-world experience, achieving a 37% success rate increase.

Ruizhe Liao, Wenrui Chen, Liangji Zeng et al.

Popcorn benchmark combines title-aligned full-movie/trailer embeddings with VLM-encoded thumbnails to evaluate visual evidence in multimodal movie recommendation.

Ali Tourani, Fatemeh Nazary, Yashar Deldjoo et al.

PRISM directly decodes instruction sets from model activations, outperforming activation-to-language baselines with 97%+ recall in security scenarios.

Gilad Gressel, Rahul Pankajakshan, Julia Diament et al.

Proposes STRP with tree convolution and inverse dilated convolution for fine-grained traffic prediction, improving accuracy by 20% and reducing training time by 30%.

Shuhao Li, Weidong Yang, Yue Cui et al.

Reasoning Arena improves reasoning models via adaptive routing and trace tournaments, achieving a 7.6% average performance boost.

Han Zhou, Adam X. Yang, Laurence Aitchison et al.

SG-OPD introduces sign-consistency gating and phased teacher sampling, improving mathematical reasoning accuracy by 1.98 and 7.50 points over standard OPD.

Haoran Xu, Hongyu Wang, Yifei Gao et al.

MotionWAM integrates video diffusion and motion models for real-time humanoid control, achieving over 30% success rate improvement.

Jia Zheng, Teli Ma, Yudong Fan et al.

OGAS method improves worst-case reliability of PDE surrogates via generative active sampling.

Pierre Cesar, Sofya Dymchenko, Abhishek Purandare et al.

IMUG-Bench evaluates UMMs on multi-turn image-text dialogues, revealing exposure bias in generation.

Lingyi Meng, Zecong Tang, Haoran Li et al.

SEF-CLGC combines logical notation with small language models, achieving a 27.80% content score.

Hanna Abi Akl, Fabien Gandon, Catherine Faron et al.

Combining P2 enhancement and quantum-inspired algorithms, the method improves UAV small-object detection AP by 31.10%.

Wuming Lei, Yanbin Gao, Mingyan Sun et al.