Knowledge catalogue
arXiv:2602.02043v2 Announce Type: replace-cross Abstract: Modern vision-language models struggle with basic compositional reasoning, failing to bind attributes to objects or relations to their referen
arXiv:2609.31470v1 Announce Type: cross Abstract: Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ signif
arXiv:2609.30738v1 Announce Type: new Abstract: KV cache eviction methods such as SnapKV and PyramidKV rank tokens solely by mean attention over a small observation window. We study a unified score, m
arXiv:2609.30747v1 Announce Type: cross Abstract: As artificial intelligence (AI) becomes embedded in everyday life, its environmental footprint, particularly water consumption remains largely invisib
arXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing
arXiv:2609.31093v1 Announce Type: new Abstract: Scaling language models to long contexts is limited by the quadratic cost of self-attention. Block sparse attention offers an efficient alternative, but
arXiv:2609.30297v1 Announce Type: cross Abstract: Conversational recommendation agents are a new paradigm for content discovery, enabling users to express complex intents through natural language (e.g
arXiv:2609.30492v1 Announce Type: cross Abstract: Language models often produce homogeneous responses to open-ended tasks; such homogeneity can spawn groupthink-the convergence of ideas toward a singu
arXiv:2609.31165v1 Announce Type: cross Abstract: Speech-breath segmentation is a fundamental preprocessing step in respiratory audio analysis, enabling applications such as respiratory acoustic bioma
arXiv:2609.31363v1 Announce Type: new Abstract: Distributionally robust optimization (DRO) provides a principled framework for learning under distribution shift, but its practical use is hindered by t
arXiv:2609.31329v1 Announce Type: new Abstract: Morphology--control co-design jointly optimizes an agent's body structure and control policy as an integrated embodied system. However, existing methods
arXiv:2609.30341v1 Announce Type: new Abstract: Data Spaces enable sovereign and governed data sharing across organizational boundaries, but their integration with AI agents remains challenging due to
arXiv:2609.30291v1 Announce Type: new Abstract: The purpose of this article is to highlight the central role of autonomous systems as the ultimate stage in the development of AI, to explain the underl
arXiv:2609.31222v1 Announce Type: new Abstract: Pocket-conditioned molecular diffusion updates ambient atom coordinates, but many lead-optimization objectives are expressed on quotient features such a
arXiv:2609.30951v1 Announce Type: new Abstract: Differentiable simulation provides analytic gradients of robot dynamics, enabling fast and sample-efficient first-order policy optimization. However, ob
arXiv:2609.30884v1 Announce Type: new Abstract: Large language models rely on KV caching to reduce repeated prefill computation in long context and interactive applications. As lightweight adapters ev
arXiv:2609.30676v1 Announce Type: new Abstract: For people who are blind, touch provides an essen-tial channel for accessing written information through Braille. Bringing a similar capability to robot
arXiv:2609.31140v1 Announce Type: new Abstract: Most Vision-Language Models (VLMs) are built by extending pretrained Large Language Models (LLMs) with visual modules and multimodal alignment. However,
arXiv:2609.30997v1 Announce Type: cross Abstract: Passive image provenance asks whether pixels alone can reveal where an image came from: a human, an aggregate AI class, or a particular generator. Thi
arXiv:2609.31540v1 Announce Type: cross Abstract: Sending every network-automation input to a third-party frontier LLM exports sensitive artifacts such as production configurations, topologies, and lo
arXiv:2609.30471v1 Announce Type: cross Abstract: Reference-based LLM-as-a-judge evaluation assumes the reference answer is the target. In deployed agentic systems that operate over dynamic entities (
arXiv:2609.30293v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) enables AI agents to discover and call tools, but loading every definition becomes expensive as connected catalogs gr
arXiv:2609.30650v1 Announce Type: cross Abstract: Task performance need not determine which intervention mechanism an agent retains. We study causal retention: whether a frozen learned state answers a
arXiv:2609.30913v1 Announce Type: new Abstract: Vision-language-action (VLA) policies can execute many tasks from standard initial states, yet a new instruction may fail after another task has altered
arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl
arXiv:2609.31326v1 Announce Type: cross Abstract: Ordinal acne severity grading requires distinguishing visually similar neighboring grades while jointly weighing holistic facial appearance and locali
arXiv:2609.31062v1 Announce Type: new Abstract: Patient-facing AI assistants promise valuable support to patients, but incoming queries can pose medical risks. To create guardrails, we work with oncol
arXiv:2609.31054v1 Announce Type: new Abstract: Large Language Model (LLM) pollution occurs when synthetic responses contaminate data intended to capture human behavior. High deployment costs have so
arXiv:2505.16326v3 Announce Type: replace Abstract: Recent years have seen rapid progress in multimodal large language models (MLLMs) in the field of chemistry. However, chemical MLLMs that can handle
arXiv:2609.31339v1 Announce Type: cross Abstract: Reconstructing environments where parts of the scene change between captured image sets poses a challenge for 3D scene reconstruction. We present Chro
arXiv:2609.31509v1 Announce Type: cross Abstract: We present ClearGS for 3D Gaussian Splatting (3DGS) from handheld videos with uneven viewpoint coverage and mixed frame quality. Rather than selecting
arXiv:2609.31014v1 Announce Type: new Abstract: Animals such as squirrels and even bears have adapted to rapidly climb up trees and other complex vertical terrain, but achieving comparable agility has
arXiv:2609.30345v1 Announce Type: cross Abstract: Cloud-security investigation is dominated by population tasks: which identities can read a data store, how many resources fail a control, which assets
arXiv:2609.31272v1 Announce Type: cross Abstract: AI is becoming increasingly integrated into daily workflows, especially in computing. We are gradually shifting towards an AI-rich future, an impendin
arXiv:2609.31418v1 Announce Type: new Abstract: A photorealistic 3D view tells a teleoperator where a robot is, but not what the scene contains, how well each object has been observed, or how to turn
arXiv:2604.04247v2 Announce Type: replace Abstract: Recent advances in prompt learning allow large language model agents to acquire task-relevant knowledge from inference-time context without paramete
arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models r
arXiv:2609.31589v1 Announce Type: new Abstract: Direct feedback alignment (DFA) trains hidden layers through fixed random projections of output error. With tanh hidden units and independent sigmoid ou
arXiv:2609.31587v1 Announce Type: cross Abstract: We investigate whether natural-language documentation helps coding agents resolve software issues, and we build the tools to construct and evaluate it
arXiv:2609.31035v1 Announce Type: new Abstract: Cooperative payload transportation using multiple extit{Unmanned Aerial Vehicles} (UAVs) poses challenges in stability, coordination, and robustness, es
arXiv:2609.31117v1 Announce Type: new Abstract: Service robots remain difficult to deploy in domestic environments, partly because fully autonomous operation is not yet reliable in unpredictable surro
arXiv:2609.31381v1 Announce Type: new Abstract: Context projection replaces older tool observations with compact, addressable excerpts, reducing repeated input while potentially adding evidence-retrie
arXiv:2609.31430v1 Announce Type: new Abstract: Tool observations dominate the context of software-engineering agents, making long interaction histories costly to maintain. Existing context compressio
arXiv:2609.30647v1 Announce Type: new Abstract: A useful visual representation is a statistic of the observed past that retains the latent factors shared with the future and discards patch-private noi
arXiv:2609.30886v1 Announce Type: cross Abstract: Conformal prediction can lose coverage when the data distribution changes after deployment. We study adaptation using labeled source data and unlabele
arXiv:2609.30796v1 Announce Type: new Abstract: Diagnostic consultation is an online sequential decision-making process in which clinicians gather evidence through patient interaction until a diagnosi
arXiv:2609.30523v1 Announce Type: new Abstract: Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-
arXiv:2609.31378v1 Announce Type: new Abstract: In recent years, diffusion models and GAN-based models have become the mainstream approaches for SAR-to-optical image translation, owing to their advant
arXiv:2609.30546v1 Announce Type: cross Abstract: In this paper, we establish the first asymptotic convergence guarantees for the Muon algorithm through a more accurate proxy for the Newton-Schultz it
arXiv:2609.31211v1 Announce Type: new Abstract: Underwater robotic inspection depends on acquiring views that reveal task-relevant structure. For a structurally complex coral colony, recognising the t
arXiv:2609.30275v1 Announce Type: new Abstract: A statistic reported without the quantity needed to interpret it is not evidence. We develop that thesis for a concrete practice in AI safety. Interpret
arXiv:2609.30360v1 Announce Type: cross Abstract: Inspired by the problem of identifying the best model from a collection of large language models (LLMs) with heterogeneous querying costs, we formulat
arXiv:2609.30811v1 Announce Type: new Abstract: Online conformal prediction can fail when predictions shape actions and actions determine which outcomes enter calibration. Standard adaptive methods ma
arXiv:2609.30974v1 Announce Type: new Abstract: Lexical semantic change is usually summarized by a scalar distance between independently sampled period distributions. This measures how much a word cha
arXiv:2609.30714v1 Announce Type: new Abstract: Agentic AI systems are increasingly being explored in medical imaging to improve throughput and reduce clinician workload; however, safe deployment rema
arXiv:2609.31149v1 Announce Type: new Abstract: Scientific measurements such as single-cell RNA (scRNA) sequencing often take the form of nonnegative integer counts, whereas continuous-state diffusion
arXiv:2609.30914v1 Announce Type: cross Abstract: Quantum-inspired algorithms emulate quantum mechanical principles, such as, superposition, interference, and probabilistic amplitude evolution, on cla
arXiv:2609.30395v1 Announce Type: new Abstract: Real-time tiny object detection in aerial imagery is constrained by the weak spatial evidence of very small objects and the loss of high-resolution deta
arXiv:2609.31232v1 Announce Type: new Abstract: Bringing an aerial robotics method from simulation to flight should not require rebuilding a mature autopilot or adding a companion computer. Cybflight
arXiv:2609.31314v1 Announce Type: new Abstract: Cytopathology detection requires open-vocabulary recognition because cellular categories are fine-grained, long-tailed, and continuously evolving across