arXiv AI
Jun 24
Multimedia and Visual Analytics in the Agentic Era
arXiv:2504. 06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Jun 24
MMed-Bench-IR: A Heterogeneous Benchmark for Multilingual Medical Information Retrieval
arXiv:2606. 24200v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) in clinical settings increasingly requires multilingual retrieval against predominantly English evidence corpora.
arXiv AI
Jun 24
MOCHA: Multi-modal Objects-aware Cross-arcHitecture Alignment
arXiv:2509. 14001v5 Announce Type: replace-cross Abstract: Personalized object detection aims to adapt a general-purpose detector to recognize user-specific instances from only a few examples.
arXiv AI
Jun 24
FP8 is All You Need (Part 2): Efficient Ozaki-Bailey Style FFT Through Tensor-core Garner Reformulation and Kulisch Escape Route
arXiv:2606. 23698v1 Announce Type: cross Abstract: NVIDIA's Blackwell Ultra (B300) cuts FP64 vector throughput to ~1.
arXiv Machine Learning
Jun 24
Project Ariadne: Prompt-Conditioned Route Generation for Synthesis Planning
arXiv:2606. 24184v1 Announce Type: new Abstract: Retrosynthetic planning seeks to connect a target molecule to commercially available starting materials through a multistep route.
arXiv AI
Jun 24
Entity Resolution via Batched Oracle Queries
arXiv:2606. 24407v1 Announce Type: cross Abstract: We consider an oracle that processes a limited batch of records at a time and clusters those that refer to the same real-world entity.
arXiv AI
Jun 24
Attention in Motion: Secure Platooning via Transformer-based Misbehavior Detection
arXiv:2512. 15503v3 Announce Type: replace-cross Abstract: Vehicular platooning promises transformative improvements in transportation efficiency and safety through the coordination of multi-vehicle formations enabled by Vehicle-to-Everything (V2X) communication.
arXiv AI
Jun 24
IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO
arXiv:2606. 23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language models on financial tasks.
arXiv AI
Jun 24
Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning
arXiv:2606. 24064v1 Announce Type: new Abstract: Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferring what to answer rather than how to reason.
arXiv AI
Jun 24
Benchmarking LLMs' Mathematical Reasoning with Unseen Random Variables Questions
arXiv:2501. 11790v5 Announce Type: replace-cross Abstract: Recent studies have raised significant concerns regarding the reliability of current mathematics benchmarks, highlighting issues such as simplistic design and potential data contamination.
arXiv Machine Learning
Jun 24
Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages
arXiv:2606. 23725v1 Announce Type: cross Abstract: Machine-learning screens for battery materials are trained and judged almost entirely against computed reference voltages, and those references carry their own systematic errors.
arXiv AI
Jun 24
ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms
arXiv:2512. 03476v3 Announce Type: replace-cross Abstract: Progress in computational science depends on complex numerical workflows that must faithfully encode physical laws, yet translating conceptual insight into reliable code remains a major bottleneck.
arXiv AI
Jun 24
VeriPilot: An LLM-Powered Verilog Debugging Framework
arXiv:2606. 23759v1 Announce Type: cross Abstract: Verilog debugging remains one of the most time-consuming stages in digital circuit design.
arXiv AI
Jun 24
Heterogeneous 2D/1D Signal Representation Fusion for Underwater Acoustic Modulation Recognition Under Distribution Shift
arXiv:2606. 23702v1 Announce Type: cross Abstract: Modulation recognition systems rely on heterogeneous signal representations.
arXiv AI
Jun 24
SemChunk-C: Semantic Segmentation for C Code
arXiv:2606. 23697v1 Announce Type: cross Abstract: Semantic segmentation of code written in a C-family language remains a challenging problem, due to the language's complex syntax, macro expansion, and irregular structural patterns.
arXiv Machine Learning
Jun 24
BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks
arXiv:2606. 24162v1 Announce Type: cross Abstract: Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics.
arXiv AI
Jun 24
Average Rankings Mask Per-Subject Optimality: A Friedman-Nemenyi Benchmark of EEG Motor-Imagery BCI Decoders
arXiv:2606. 24394v1 Announce Type: cross Abstract: Electroencephalography (EEG) is the dominant non-invasive modality for brain-computer interfaces (BCIs), yet reliable decoding of motor imagery is hampered by inter- and intra-individual variability.
arXiv AI
Jun 24
A specialized reasoning large language model for accelerating rare disease diagnosis: a randomized AI physician assistance trial
arXiv:2606. 24510v1 Announce Type: new Abstract: Rare diseases affect millions of individuals worldwide, yet timely diagnosis remains a major public health challenge due to scarcity of specialized clinical expertise.
arXiv AI
Jun 24
FLUX3D: High-Fidelity 3D Gaussian Generation with Diffusion-Aligned Sparse Representation
arXiv:2606. 24874v1 Announce Type: cross Abstract: Sparse voxel representation has emerged as a scalable foundation for image-to-3D Gaussian Splatting (3DGS) generation, yet current methods struggle to preserve high-frequency visual details of input images due to two structural bottlenecks.
arXiv AI
Jun 24
Metis: Bridging Text and Code Memory for Self-Evolving Agents
arXiv:2606. 24151v1 Announce Type: cross Abstract: Self-evolving agents improve over time by distilling experience from past executions and reusing it in future tasks.