Knowledge catalogue
arXiv:2609.03635v1 Announce Type: new Abstract: Clinical trials in the UK can cost up to {pounds}1.3 million, with approximately 90% drug failure rate. Toxicity is a major contributing factor in drug
arXiv:2206.05215v2 Announce Type: replace Abstract: K-Means clustering algorithm is one of the most commonly used clustering algorithms because of its simplicity and efficiency. K-Means clustering alg
arXiv:2604.17000v1 Announce Type: cross Abstract: The growing reliance on large-scale speech data has made privacy protection a critical concern. However, existing anonymization approaches often degra
arXiv:2511.15884v2 Announce Type: replace-cross Abstract: Recovering the 9D pose of objects, both their 6D pose and 3D dimensions, under clutter and occlusion is a core requirement for warehouse autom
arXiv:2603.16718v2 Announce Type: replace Abstract: LLMs perform strongly across NLP, but their ability to produce explicit grammatical analyses remains unclear. Arabic provides a challenging testbed
arXiv:2609.03668v1 Announce Type: new Abstract: Accurate segmentation of corneal layers in optical coherence tomography (OCT) is essential for quantitative assessment of corneal morphology, including
arXiv:2609.03716v1 Announce Type: new Abstract: Data centers are increasingly optimized by artificial intelligence and, at the same time, increasingly loaded by it. The literature treats these as two
arXiv:2609.03362v1 Announce Type: new Abstract: Grasping and holding tools while using them presents a considerable challenge not only for robots but also for humans. Such a challenge is particularly
arXiv:2607.15565v2 Announce Type: replace-cross Abstract: Where should the question go in a vision-language model (VLM) prompt: before the image or after it? Intuition says before: knowing what is ask
arXiv:2511.20591v3 Announce Type: replace Abstract: The emergence and evolution of feature reliance in deep reinforcement learning agents remain poorly understood. Here, we introduce a methodological
arXiv:2602.09341v2 Announce Type: replace Abstract: Multi-agent systems (MAS) can substantially extend the reasoning capacity of large language models (LLMs). Most MAS frameworks aggregate agent outpu
arXiv:2609.03615v1 Announce Type: new Abstract: While deep generative models offer new opportunities for medical image synthesis and data sharing, their ability to memorize and reproduce training samp
arXiv:2609.03478v1 Announce Type: new Abstract: We report on our ongoing project to develop a computational pipeline, AutoGraphForge, for an automated graph-theoretic conjecturing-refuting-formalizing
arXiv:2609.03970v1 Announce Type: new Abstract: Accurate identification of weld seam geometries is essential for automated robotic post processing operations such as grinding, finishing, and inspectio
arXiv:2609.03239v1 Announce Type: new Abstract: In the one-time selling B2B context, the buying cycle may last months or even years. During the long process, targeting customers that have a high poten
arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t
arXiv:2601.22931v2 Announce Type: replace Abstract: The prevalence of rapidly evolving slang, neologisms, and highly stylized expressions in informal user-generated text, particularly on Chinese socia
arXiv:2606.09655v2 Announce Type: replace Abstract: Despite remarkable progress in machine translation (MT), non-AI communities have raised growing concerns about MT systems, suggesting a noticeable g
arXiv:2609.03734v1 Announce Type: cross Abstract: BLEU-4 is the standard metric for evaluating sign language translation (SLT), but spoken-language metrics may not adequately reflect sign language pro
arXiv:2609.03095v1 Announce Type: cross Abstract: Smartphone skin photographs are indispensable to teledermatology, yet assessing the diagnostic suitability of submitted cases (gradability) remains a
arXiv:2609.03900v1 Announce Type: new Abstract: Continual knowledge-updating methods are often declared superior from one final checkpoint and one conventional adapter rank. We show that this can be i
arXiv:2609.03460v1 Announce Type: new Abstract: As generative AI makes polished prose cheap to produce, users can no longer rely on fluency as a proxy for truth. We call this failure mode the Fluency
arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat
arXiv:2605.06508v2 Announce Type: replace-cross Abstract: Research artifacts are widely shared to support reproducibility, and artifact evaluation (AE) has become common at many leading conferences. H
arXiv:2609.04131v1 Announce Type: new Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual inputs and respond to user queries under st
arXiv:2609.03887v1 Announce Type: new Abstract: How do the methods used to train language models to refuse harmful requests shape how that refusal actually works inside the model? We compare three pos
arXiv:2609.03139v1 Announce Type: new Abstract: Deep neural networks (DNNs) are increasingly deployed in real-world vision systems, yet their predictions can be covertly manipulated by backdoor attack
arXiv:2609.03443v1 Announce Type: new Abstract: The performance of Flow Matching largely depends on the quality of the coupling between the source and target distributions. However, independent coupli
arXiv:2609.03320v1 Announce Type: cross Abstract: Remote voice studies often retain a final audio file with limited evidence about how it was captured, transferred, processed, and accepted. This paper
arXiv:2609.02895v1 Announce Type: new Abstract: Large-scale public events, such as religious festivals, political rallies, and cultural gatherings, are increasingly vulnerable to the rapid disseminati
arXiv:2609.03871v1 Announce Type: new Abstract: Large language model agents have shown promise in bioinformatics, but most existing systems focus primarily on producing final answers, treating plannin
arXiv:2609.03463v1 Announce Type: new Abstract: Automated pig monitoring is essential for assessing their health, behaviour, and welfare. To date, most pig monitoring solutions operate on the group-le
arXiv:2609.04120v1 Announce Type: new Abstract: Video virtual try-on (VVT) aims to generate realistic videos of a person wearing a target garment. Recent methods leverage a keyframe-driven video gener
arXiv:2609.02890v1 Announce Type: new Abstract: A personalized language agent must convert a user's interaction history into behavior on each new request at inference time. Two strategies dominate. Re
arXiv:2609.03497v1 Announce Type: cross Abstract: Developing humanoid robots capable of leveraging human behavioral data is essential for general-purpose embodiment, yet conventional development remai
arXiv:2609.03502v1 Announce Type: cross Abstract: In low-resource settings, deploying TTS typically requires choosing between a large voice-cloning model with costly inference or a compact fixed-voice
arXiv:2609.03557v1 Announce Type: new Abstract: Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene transit
arXiv:2509.15677v2 Announce Type: replace Abstract: We propose Camera Splatting, a novel view optimization framework for novel view synthesis. Each camera is modeled as a 3D Gaussian, referred to as a
arXiv:2609.03721v1 Announce Type: cross Abstract: Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented
arXiv:2604.17125v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) widens the prompt injection attack surface of large language model applications to tool descriptions, paramet
arXiv:2609.03995v1 Announce Type: cross Abstract: Verifying that manufactured batches of milling tools or carbide rotary burrs conform to production order sheets remains a largely manual and error-pro
arXiv:2609.03407v1 Announce Type: new Abstract: People increasingly turn to large language models (LLMs) for everyday advice, making ethically charged interpersonal problems a practical moral-advisory
arXiv:2509.14435v3 Announce Type: replace Abstract: Large language models (LLMs) have transformed natural language processing (NLP), enabling diverse applications by integrating large-scale pre-traine
arXiv:2609.03003v1 Announce Type: new Abstract: Causal inference is the practice of estimating the effect of a treatment or intervention from data. It traditionally requires a bespoke pipeline for eve
arXiv:2609.03818v1 Announce Type: new Abstract: Collaborative perception enhances environment understanding through multi-agent information sharing, but its performance in real-world scenarios is cons
arXiv:2609.03394v1 Announce Type: new Abstract: Emotion recognition benchmarks often predict one emotion per text, missing many real-world scenarios where two people arrive at opposing emotions from a
arXiv:2609.04198v1 Announce Type: new Abstract: Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rare
arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con
arXiv:2609.03973v1 Announce Type: new Abstract: An image editor may satisfy every regional plausibility constraint separately even when no single latent explanation fits the complete output. We formal
arXiv:2609.03901v1 Announce Type: cross Abstract: We present a comparative evaluation of six information retrieval methods for the task of academic advisor discovery: ranking CS faculty members by rel
arXiv:2609.04199v1 Announce Type: cross Abstract: Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduce
arXiv:2602.00266v2 Announce Type: replace Abstract: Two deep ReLU networks can have entirely different architectures and parameters, yet realize the same function. We provide a complete characterizati
arXiv:2609.03389v1 Announce Type: cross Abstract: Smectic liquid crystals are layered liquid-crystalline phases characterized by orientational order and periodic density modulation. Although their str
arXiv:2609.03895v1 Announce Type: new Abstract: Dust in agriculture presents a significant challenge for autonomous agricultural machinery. Dust can impair the performance of sensors and algorithms. T
arXiv:2609.04090v1 Announce Type: new Abstract: Current conditioned generative models heavily rely on score functions for guidance during training. When the generative model is a diffusion process wit
arXiv:2609.04113v1 Announce Type: new Abstract: We introduce an uncoupled learning algorithm which, when employed by all players of an arbitrary N-player normal form game with up to K actions per play
arXiv:2609.02899v1 Announce Type: new Abstract: Benchmark contamination, the leakage of test items into training data, is widely described as a threat to the reliability of large language model (LLM)
arXiv:2609.03273v1 Announce Type: new Abstract: Tamil spell and grammar correction is challenging because Tamil is an agglutinative low-resource language with rich verbal morphology, complex sandhi (p
arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a
arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent