Knowledge catalogue
arXiv:2604.17278v1 Announce Type: new Abstract: Effective pest recognition and management are crucial for sustainable agricultural development. However, collecting pest data in real scenarios is often
arXiv:2502.02871v2 Announce Type: replace Abstract: Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, i
arXiv:2505.19237v2 Announce Type: replace-cross Abstract: Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, auto
arXiv:2510.13759v3 Announce Type: replace Abstract: Unified multimodal models aim to jointly enable visual understanding and generation, yet current benchmarks rarely examine their true integration. E
arXiv:2603.23404v2 Announce Type: replace-cross Abstract: Existing Multimodal Large Language Models (MLLMs) struggle with 3D spatial reasoning, as they fail to construct structured abstractions of the
arXiv:2604.16054v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have achieved impressive progress on vision language benchmarks, yet their capacity for visual cognitive and
arXiv:2604.14306v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated high proficiency on English-centric medical examinations, their performance often declines when fac
arXiv:2604.15210v1 Announce Type: cross Abstract: Humor is one of the few cognitive tasks where getting the reasoning right matters as much as getting the answer right. While recent work evaluates hum
In this post, we show you how to build a video semantic search solution on Amazon Bedrock using Nova Multimodal Embeddings that intelligently understands user intent and retrieves accurate video resul
arXiv:2509.15602v5 Announce Type: replace Abstract: Multimodal large language models (MLLMs) excel at general video understanding but struggle with fast, high-frequency sports like tennis, where rally
arXiv:2604.14044v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general vision-language tasks, their application to remote sensing change understanding is hinde
This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models (NADPFM) at ICLR 2026. Principled domain reweighting can substantially improve sample efficienc
arXiv:2604.13252v1 Announce Type: new Abstract: Anomaly detection aims to identify observations that deviate from expected behavior. Because anomalous events are inherently sparse, most frameworks are
We’re open-sourcing HY-World 2.0, a multimodal world model that generates, reconstructs, and simulates interactive *3D worlds* from text, images, and videos. Outputs can be integrated into game engine
arXiv:2604.12735v1 Announce Type: new Abstract: LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this p
arXiv:2604.12081v1 Announce Type: new Abstract: Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the con
arXiv:2604.12970v1 Announce Type: cross Abstract: Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge
arXiv:2604.12319v1 Announce Type: new Abstract: Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multi
arXiv:2604.11835v1 Announce Type: cross Abstract: Machine learning for tabular data remains constrained by poor schema generalization, a challenge rooted in the lack of semantic understanding of struc
arXiv:2604.10973v1 Announce Type: new Abstract: Reasoning over tabular data is a crucial capability for tasks like question answering and fact verification, as it requires models to comprehend both fr
arXiv:2604.10219v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoni
arXiv:2509.25866v2 Announce Type: replace Abstract: The 'thinking with images' paradigm represents a pivotal shift in the reasoning of Vision Language Models (VLMs), moving from text-dominant chain-of
arXiv:2604.11299v1 Announce Type: cross Abstract: In recent years, rapid advances in Multimodal Large Language Models (MLLMs) have increasingly stimulated research on ancient Chinese scripts. As the e
arXiv:2603.22911v2 Announce Type: replace-cross Abstract: Due to the great saving of computation and memory overhead, token compression has become a research hot-spot for MLLMs and achieved remarkable
arXiv:2604.09907v1 Announce Type: cross Abstract: To improve crop genetics, high-throughput, effective and comprehensive phenotyping is a critical prerequisite. While such tasks were traditionally per
arXiv:2506.14170v3 Announce Type: replace-cross Abstract: Accurate quantification of fish feeding intensity is crucial for precision feeding in aquaculture, as it directly affects feed utilization and
arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less
Tencent's HunyuanWorld is an open-source multimodal 3D world generation model from the Tencent Hunyuan team, featuring 360° immersive experiences via panoramic world proxies, mesh export capabilities
arXiv:2508.16165v2 Announce Type: replace-cross Abstract: Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relie
arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to
arXiv:2604.09473v1 Announce Type: new Abstract: Fully immersive experiences that tightly integrate 6-DoF visual and auditory interaction are essential for virtual and augmented reality. While such exp
arXiv:2604.08815v1 Announce Type: new Abstract: Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-re
arXiv:2604.08545v1 Announce Type: new Abstract: The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a pro
arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th
arXiv:2604.08063v1 Announce Type: new Abstract: Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due to its low spatial resolution and high noise, parti
arXiv:2604.08418v1 Announce Type: new Abstract: Inspired by the human ability to understand and predict others, we study the applicability of Conditional Neural Processes (CNP) to the task of self-sup
arXiv:2604.06985v1 Announce Type: cross Abstract: Frailty and functional decline strongly influence treatment tolerance and outcomes in older patients with cancer, yet assessment is typically limited
arXiv:2509.09794v4 Announce Type: replace Abstract: Computational models have emerged as powerful tools for multi-scale energy modeling research at the building and urban scale, supporting data-driven
arXiv:2604.06901v1 Announce Type: cross Abstract: Conventional career guidance platforms rely on static, text-driven interfaces that struggle to engage users or deliver personalised, evidence-based in
Highlights: 👉 Configurable thinking mode for step-by-step reasoning 👉 Multimodal understanding with text and image input, including document parsing and OCR 👉 Native function calling with structured t
arXiv:2506.03371v2 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have enabled accurate image-based geolocation, raising serious concerns about location privacy risk
arXiv:2610.21686v1 Announce Type: new Abstract: Reliable contact-rich manipulation requires detecting execution deviations early enough for corrective action. Yet most monitoring methods are reactive,
arXiv:2610.15239v1 Announce Type: new Abstract: Most benchmarks for large language models in medicine are built from licensing examinations and theoretical questions. The few that draw on real clinica
arXiv:2610.16038v1 Announce Type: cross Abstract: E-commerce user preferences evolve dynamically within sessions, exhibiting concurrent and multi-centric interest distributions. While existing multimo
arXiv:2610.16569v1 Announce Type: cross Abstract: Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance lab
arXiv:2610.17937v1 Announce Type: new Abstract: Table reasoning with language models typically assumes access to clean textual tables. In practice, tables are often serialized into text, which can cor
arXiv:2610.18447v1 Announce Type: cross Abstract: World models have emerged as a promising paradigm for embodied AI, yet existing systems often remain fragmented in the modalities they model and the f
arXiv:2610.16441v1 Announce Type: new Abstract: Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Explai
arXiv:2610.13128v1 Announce Type: new Abstract: Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-
We are expanding the Clef decision model family with Clef-omni, natively processing audio, video, images, and text in a single pipeline. We’ve also lowered Clef-flash pricing and boosted Clef inferenc
arXiv:2609.12035v3 Announce Type: replace Abstract: Cardiovascular diagnosis and treatment rest on integrating complementary modalities, such as electrocardiogram, echocardiography, and chest X-rays,
arXiv:2610.08985v1 Announce Type: cross Abstract: The aim of processing and analyzing experimental data from physical experiments is to obtain physically significant information about the phenomenon u
arXiv:2610.06830v1 Announce Type: cross Abstract: Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent me
arXiv:2610.02722v1 Announce Type: new Abstract: Structural connectivity (SC) and functional connectivity (FC) provide complementary information on interactions between brain regions and are widely use
arXiv:2609.39072v1 Announce Type: cross Abstract: Emotion recognition in conversation has been widely studied, but applying Large Language Models (LLMs) to continuous dimensional emotion evaluation in
arXiv:2603.08459v2 Announce Type: replace Abstract: Safe predictions are a crucial requirement for integrating predictive models into clinical decision support systems. One approach to improving trust
arXiv:2609.38523v1 Announce Type: cross Abstract: Financial forecasting from earnings conference calls requires models to reason over complex corporate disclosures, market expectations, and subtle com
arXiv:2609.37923v1 Announce Type: new Abstract: Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce Ep
arXiv:2609.36850v1 Announce Type: new Abstract: Generative content is increasingly entering the production and dissemination of news, transforming fake news from manually fabricated or simply manipula
arXiv:2609.36502v1 Announce Type: cross Abstract: Past research using log data has faced the 'learning system wall,' whereby few methods exist for generalizing models of student learning across platfo