Benchmarks and evaluation

Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.

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arXiv Machine Learning

Sep 22

Learning Dynamic Neural Evidence Representations for Time-Adaptive Brain-Computer Interfaces

arXiv:2609.22088v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) decode neural activity into commands, yet most existing systems rely on fixed-window decoding that may result in red...

By Beining Cao, Ziyi Zhao, Xiaowei Jiang, Daniel Leong, Yingtao Ren, Thomas Do, Yu-Cheng Fred Chang, Chin-Teng Lin

rag benchmarks

arXiv Machine Learning

Sep 22

AdaMem: Adaptive Memory Token Allocation for Soft Compression in Retrieval-Augmented Generation

arXiv:2609.22100v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves language models with retrieved evidence, but processing many long passages is costly and can introduce...

By Artem Sakhno, Grigorii Davydenko, Omar Zoloev, Julia Belikova, Andrey Savchenko, Maksim Makarenko

llms rag efficiency benchmarks

arXiv Machine Learning

Sep 22

ST-Topo GAN: A Motor EEG-to-EMG Decoding Model Matched to Wrist Movement Complexity

arXiv:2609.22128v1 Announce Type: cross Abstract: The wrist plays a critical role in upper-limb function by enabling precise hand positioning, force regulation, and object manipulation. Continuous br...

By Ye Sun, Mingxuan Qu, Jing Wang, Dezhong Yao, Gang Liu

diffusion robotics benchmarks safety

arXiv Machine Learning

Sep 22

DiFA: Dual Evidence Fusion and Aggregation for Token-Level Text Anomaly Detection

arXiv:2609.22136v1 Announce Type: cross Abstract: Text anomaly detection, the task of identifying text instances that deviate from normal language patterns, is crucial for language-driven application...

By Yanyu Qian, Pengcheng Weng, Yue Tan, Enguang Zuo, Yu Zheng, Yixin Liu

benchmarks safety

arXiv Machine Learning

Sep 22

HFEMCNet: A Compact Hybrid Frequency Enriched Multi Channel Network for Automatic Modulation Classification

arXiv:2609.22139v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) of received radio signals is prudent for further signal processing tasks such as communication monitoring,...

By Qamar Ijaz, Nayyer Aafaq

efficiency benchmarks

arXiv Machine Learning

Sep 22

Attention-Enhanced Dual-Branch ConvNeXt-BiLSTM Network for Subject-Independent EEG Seizure Detection

arXiv:2609.22141v1 Announce Type: cross Abstract: Automated seizure detection from scalp electroencephalography (EEG) is difficult because seizure morphology varies among patients and seizure samples...

By Maimuna Chowdhury, Sk. Imran Hossain

computer-vision efficiency benchmarks

arXiv Machine Learning

Sep 22

ECP-Bench: Benchmarking and Learning Entertainment Content Promotion with Foundation Models

arXiv:2609.22150v1 Announce Type: cross Abstract: Content promotion spans a broad set of skills, from understanding content to forecasting its market reception. However, LLMs' ability to support such...

By Hyomin Kim, Bowen Chen, Jin Huang, Zhao Wang, Qiaozhu Mei, Shingo Takamatsu

llms fine-tuning benchmarks

arXiv Machine Learning

Sep 22

Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation

arXiv:2609.22162v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generatio...

By Can Peng, Yu Liu, Yingyu Yang, Anjie Le, Yuyuan Liu, Qianye Yang, J. Alison Noble

llms rag nlp multimodal benchmarks

arXiv Machine Learning

Sep 22

Quantifying Hidden Salt for Precision Healthcare: Sodium Assessment via Joint-Factor Retrieval and Chain-of-Thought Inference

arXiv:2609.22171v1 Announce Type: cross Abstract: Precision healthcare, particularly for conditions like hypertension and cardiovascular disease, necessitates monitoring of dietary sodium intake. How...

By Mingyu Huang, Weiqing Min, Yuehui Fang, Yuna He, Shuqiang Jiang

llms rag benchmarks

arXiv Machine Learning

Sep 22

Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems

arXiv:2609.22189v1 Announce Type: cross Abstract: The Schrodinger equation in one spatial dimension admits a small set of exactly solvable potentials that serve as natural proving grounds for any new...

By Tariq Mahmood, Waqas Arshad, Bilal Naseer, Alfredo Raya

rag benchmarks

arXiv Machine Learning

Sep 22

Dissecting Training-Free Uncertainty Estimation in Multimodal Large Language Models

arXiv:2609.22206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of multimodal tasks, yet understanding and quantify...

By Soroush Seifi, Vaggelis Dorovatas, Lin Li, Yarin Gal, Rahaf Aljundi

llms multimodal benchmarks safety

arXiv Machine Learning

Sep 22

Assessing Adversarial Robustness of Latent Reasoning Models

arXiv:2609.22228v1 Announce Type: cross Abstract: Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings subst...

By Shaolong Chen, Ang Li, Mingjie Li, Yisen Wang

llms multimodal benchmarks safety

arXiv Machine Learning

Sep 22

Learning and Control Beyond Linearity: Towards a Non-asymptotic Theory for Bilinear Systems

arXiv:2609.22338v1 Announce Type: cross Abstract: This tutorial provides a unified view of the emerging area of bilinear learning and control. Using linear systems as a benchmark, it explains what fu...

By Yahya Sattar, Yassir Jedra, Robin Str\"asser, Frank Allg\"ower, Maryam Fazel, Sarah Dean

reinforcement-learning benchmarks

arXiv Machine Learning

Sep 22

Mask-Aware Execution for Efficient JEPA Training

arXiv:2609.22674v1 Announce Type: cross Abstract: Joint Embedding Predictive Architectures (JEPAs) are becoming a core representation-learning primitive and a building block for latent world models a...

By Md Musfiqur Rahman Sanim, Zhihao Shu, Bahram Afsharmanesh, Amirali Mirian, Wei Niu, Gagan Agrawal

rag efficiency benchmarks

arXiv Machine Learning

Sep 22

Beyond Final-Token Classification: Heterogeneous Readouts for Evidence-Grounded Suicide Risk Detection

arXiv:2609.22767v1 Announce Type: cross Abstract: The IEEE BigData Cup benchmark combines three prediction problems with different output structures: ordinal suicide-risk classification, multi-label...

By Zirui Li, Yanling Li, Kaolanglang Gao

fine-tuning benchmarks

arXiv Machine Learning

Sep 22

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajector...

By Muhammad Abdur Rab Siddiqui, Daniela Rojas, Chen Yang, Wenqi Cui, Yuanyuan Shi, Yize Chen

llms agents fine-tuning benchmarks

arXiv Machine Learning

Sep 22

Why Do Video Diffusion Models Violate Physics? Unveiling the Flaws in Attention Mechanisms

arXiv:2609.23658v1 Announce Type: cross Abstract: Despite impressive visual quality, state-of-the-art video diffusion models often generate content that violates real-world physical laws. While exist...

By Yueyan Li, Haibo Wang, Caixia Yuan, Xiaojie Wang

rag diffusion benchmarks safety

arXiv Machine Learning

Sep 22

TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701v1 Announce Type: cross Abstract: Probabilistic forecasting requires accurate central predictions and calibrated uncertainty estimates. This paper presents TEMPER, the Temporal Encode...

By Giancarlo Vercellino

benchmarks

arXiv Machine Learning

Sep 22

SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773v1 Announce Type: cross Abstract: Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under u...

By Ke Xiao, Qiyuan Wang, Christos Anagnostopoulos

benchmarks

arXiv Machine Learning

Sep 22

Cost-Accuracy Trade-offs: Neural Operator vs Classical Numerical Solver

arXiv:2609.24021v1 Announce Type: cross Abstract: Neural operators are data-driven models that learn mappings from inputs that parameterize partial differential equations, such as spatially varying c...

By Daniel Zhengyu Huang, Andrew M. Stuart

benchmarks

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