Knowledge catalogue
arXiv:2608.18469v1 Announce Type: cross Abstract: Lightweight proxy models enable rapid experimentation without repeatedly training frontier-scale systems, but their small kernels often leave modern a
arXiv:2602.05887v3 Announce Type: replace Abstract: Low-rank matrix sensing is a fundamental yet challenging nonconvex problem whose optimization landscape typically contains numerous spurious local m
arXiv:2608.19047v1 Announce Type: new Abstract: We present Eureka, a task-conditioned Meta-Agent architecture that compiles long-horizon tasks into dynamic obligation graphs with explicit acceptance s
arXiv:2608.18690v1 Announce Type: cross Abstract: The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with th
arXiv:2608.18833v1 Announce Type: new Abstract: Medical vision-language models (VLMs) can achieve high accuracy but remain unreliable: they are systematically overconfident, benefit little from test-t
arXiv:2608.18539v1 Announce Type: cross Abstract: The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes
arXiv:2512.14629v2 Announce Type: replace-cross Abstract: Music editing plays a vital role in modern music production, with applications in film, broadcasting, and game development. Recent advances in
arXiv:2608.18289v1 Announce Type: new Abstract: The extraction of structured information from unstructured documents represents a critical component of digital transformations in all sectors. While pr
arXiv:2608.18624v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are becoming a powerful tool for many environmental monitoring and transport applications. Yet, their reliance on Global
arXiv:2608.18632v1 Announce Type: new Abstract: Aerial nadir video combines weak geometric constraints with severe perceptual aliasing, making it a difficult regime for monocular SLAM. We benchmark fi
arXiv:2605.06185v2 Announce Type: replace Abstract: Large vision-language models perform well on short- and medium-length video understanding but still struggle to maintain coherent event memory and r
arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leav
arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning
arXiv:2508.13068v2 Announce Type: replace Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address
arXiv:2608.18580v1 Announce Type: new Abstract: Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples a
arXiv:2608.18181v1 Announce Type: cross Abstract: Selecting a small, diverse subset from a large candidate pool often means balancing several incompatible notions of diversity. In trademark curation,
arXiv:2608.18296v1 Announce Type: cross Abstract: As CGM-based AI tools approach clinical deployment, whether their accuracy is equitable across patient demographics remains insufficiently tested. To
arXiv:2608.18881v1 Announce Type: new Abstract: Autoregressive perception models trained to localize visual entities under the open-vocabulary setting are mostly trained using Supervised fine-tuning (
arXiv:2510.15483v3 Announce Type: replace-cross Abstract: We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given cl
arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela
arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s
arXiv:2608.18736v1 Announce Type: new Abstract: Federated training enables language models to learn from distributed private text, but the server cannot directly verify the local supervision or optimi
arXiv:2608.18361v1 Announce Type: new Abstract: Figurative language is deeply culturally embedded; fluent use requires not just linguistic competence but cultural immersion. We ask whether LLMs can le
arXiv:2602.02060v2 Announce Type: replace-cross Abstract: Multimodal foundation models integrate heterogeneous signals across modalities, yet it remains unclear whether their predictions can be contro
arXiv:2608.19174v1 Announce Type: cross Abstract: This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate tw
arXiv:2608.18534v1 Announce Type: new Abstract: Large language models are increasingly used to support financial operations, but their apparent reasoning performance can depend on whether they receive
arXiv:2608.18099v1 Announce Type: new Abstract: Investment management is a high-stakes domain in which agentic AI systems must do more than generate plausible text. They must retrieve point-in-time da
arXiv:2606.22361v2 Announce Type: replace-cross Abstract: Why do multilingual language models sometimes generate in the wrong language, and why is this so hard to fix? We introduce Language Identity H
arXiv:2608.18733v1 Announce Type: cross Abstract: We present Flama, an open-source Python framework for developing and deploying production-ready web APIs, machine learning services, and large-languag
arXiv:2608.18656v1 Announce Type: new Abstract: Inference with transformer models on CPUs is increasingly important, especially for Small Language Models (SLMs), where vector architectures are emergin
arXiv:2608.18148v1 Announce Type: cross Abstract: We study data-driven prediction of coarse-grained dynamics in multiscale PDE systems. Adopting a closure-free operator-learning viewpoint, we apply a
arXiv:2608.18423v1 Announce Type: new Abstract: Language model agents now execute bounded tasks reliably. Whether they can sustain effective decision-making over long horizons, where actions have cumu
arXiv:2608.18993v1 Announce Type: new Abstract: Electronic travel aids are pivotal for the independent mobility of the visually impaired. While Vision-Language Models (VLMs) offer rich environmental u
arXiv:2608.18803v1 Announce Type: cross Abstract: Efficient continual learning remains a fundamental challenge for deep neural networks. While catastrophic forgetting and loss of plasticity are widely
arXiv:2608.18445v1 Announce Type: cross Abstract: We present the first mechanised formalisation of Romanov's Triplet Logic (TLS) in the Rocq proof assistant. TLS is a triplet-based combinatorial frame
arXiv:2512.05092v2 Announce Type: replace-cross Abstract: Although diffusion models now occupy a central place in generative modeling, introductory treatments commonly assume Euclidean data and seldom
arXiv:2608.18098v1 Announce Type: cross Abstract: Key-value (KV) caching is essential for efficient autoregressive inference in transformer based dialog systems, yet existing strategies treat all cach
arXiv:2608.18679v1 Announce Type: new Abstract: Structured documents such as invoices, forms, reports, and scientific articles derive meaning from the interplay between spatial layout, textual content
arXiv:2608.18136v1 Announce Type: new Abstract: Conversational agents now act for end users through tools while holding access to customer databases and internal policy documents that a caller can rea
arXiv:2608.18097v1 Announce Type: new Abstract: We present FrenchNews-7, a cross-publisher France-based French-language news editorial desk classification benchmark combining a large multi-outlet corp
arXiv:2608.18339v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities yet remain sensitive to real-world distribution shifts during infere
arXiv:2502.00735v4 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulne
arXiv:2608.18581v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) encode rich factual knowledge in their parameters, reliably recalling and verifying such knowledge remains a key
arXiv:2608.19011v1 Announce Type: cross Abstract: Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution
arXiv:2608.18968v1 Announce Type: new Abstract: Localized image edits can change a photograph's meaning while leaving most of it authentic, so forensic analysis must identify where an edit occurred. W
arXiv:2509.19893v3 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a key driver of post-training for complex reasoning in large language models (LLMs), yet online RL introd
arXiv:2608.18969v1 Announce Type: new Abstract: We consider the problem of classification of skin tone using photoplethysmography (PPG) signals with labels of the ordinal six-class Fitzpatrick skin to
arXiv:2608.18254v1 Announce Type: new Abstract: Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic
arXiv:2608.18522v1 Announce Type: cross Abstract: Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the rece
arXiv:2608.18849v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong performance through in-context learning, but context-dependent inference imposes substantial latency and
arXiv:2503.08484v2 Announce Type: replace Abstract: With the rapid development of image synthesis techniques, AI-generated images have become increasingly realistic, which heightens the potential risk
arXiv:2608.19055v1 Announce Type: new Abstract: Music-driven character animation enables and enhances transformative applications in entertainment and interactive education. However, synthesizing real
arXiv:2608.18238v1 Announce Type: new Abstract: Genomic analysis on viruses such as SARS-CoV-2 variants: Beta, Gamma, Delta, and Omicron is heavily dominated by classical bioinformatics methods, inclu
arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transforma
arXiv:2608.19141v1 Announce Type: cross Abstract: Neural audio codecs based on Residual Vector Quantization (RVQ) have become the dominant discrete representation for token-based general audio generat
arXiv:2608.18234v1 Announce Type: cross Abstract: Whole-body motion tracking policies turn a humanoid into a robust control interface: the teleoperator---or an upstream model---only supplies a coarse
arXiv:2608.18268v1 Announce Type: cross Abstract: Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumptio
arXiv:2608.18122v1 Announce Type: cross Abstract: This report presents the methodology of the Global Index on Responsible AI (GIRAI), 2nd Edition. This edition refines the 1st Edition by strengthening
arXiv:2608.18324v1 Announce Type: new Abstract: Machine-verifiable workflows produce governance records linking a task contract, model attempt, verifier decision, accepted output, and target origin. W
arXiv:2608.18996v1 Announce Type: cross Abstract: Visual grounding in Unmanned Aerial Vehicle (UAV) imagery aims to localize a target object in complex bird's-eye-view scenes according to a natural la