Knowledge catalogue
arXiv:2608.15897v1 Announce Type: new Abstract: Robot sensor designs, particularly tactile sensors, are highly diverse and evolve rapidly. Modeling each sensor in simulation demands substantial domain
arXiv:2608.15055v1 Announce Type: new Abstract: Hypergraphs effectively model higher-order groupwise relationships beyond pairwise interactions, while pretrained language models (PLMs) and large langu
arXiv:2608.14728v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an effective paradigm for transferring knowledge between language models, where a student is trained to al
arXiv:2608.14675v1 Announce Type: cross Abstract: While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethys
arXiv:2608.15763v1 Announce Type: new Abstract: AI-powered digital-avatar streamers in live e-commerce must answer product questions, engage viewers, and execute changing business strategies in real t
arXiv:2608.14641v1 Announce Type: new Abstract: Agentic systems increasingly delegate model selection to a router, yet open-source routers are usually evaluated with different tasks, candidate pools,
arXiv:2608.16345v1 Announce Type: new Abstract: Pre-trained models (PTMs) provide a strong foundation for continual learning by offering stable representations that facilitate lightweight adaptation t
arXiv:2608.14789v1 Announce Type: new Abstract: Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency reques
arXiv:2608.16742v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable progress in code generation, yet ensuring correctness in complex, repository-level tasks remains
arXiv:2608.15341v1 Announce Type: new Abstract: Text-to-image diffusion models can be misused to generate harmful content through adversarial or paraphrased prompts that bypass built-in safety mechani
arXiv:2608.15768v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free coverage guarantees and has emerged as a principled tool for uncertainty quantification. In edge-
arXiv:2608.15509v1 Announce Type: cross Abstract: Task guided agents demonstrate strong performance in a wide range of complex tasks. However, most existing task representation algorithms are tailored
arXiv:2608.15211v1 Announce Type: new Abstract: Training high-resolution AI-based Earth forecasting models is memory-intensive. Window-based Swin Transformers reduce the quadratic cost of global atten
arXiv:2608.14759v1 Announce Type: cross Abstract: Whole Slide Image (WSI) analysis has been widely studied for cancer diagnosis. Conventionally, a gigapixel WSI is divided into small patches and proce
arXiv:2608.15832v1 Announce Type: new Abstract: As AI systems become increasingly capable of autonomous action, determining whether an agent is technically capable of performing an action is insuffici
arXiv:2608.15326v1 Announce Type: new Abstract: Artificial intelligence (AI) benchmarks are not neutral tools of evaluation but socio-technical artefacts that shape competition, power, and research pr
arXiv:2608.16861v1 Announce Type: cross Abstract: We initiate a polyhedral study of the graph multi-separator problem proposed by Irmai et al. (2024) as an alternative to the lifted multicut problem f
arXiv:2608.16096v1 Announce Type: cross Abstract: Enterprises connect language models to their own data through retrieval. The benchmarks that rank multi-hop retrieval systems leave out two facts a bu
arXiv:2608.15215v1 Announce Type: cross Abstract: Token-level knowledge distillation (KD) matches two conditional distributions per position, yet the standard objectives compare them pointwise: a Kull
arXiv:2608.16710v1 Announce Type: new Abstract: As autonomous vehicles (AVs) approach Level 4 and Level 5 operational capability [SAE International, 2018], their on- board decision systems must handle
arXiv:2601.03222v2 Announce Type: replace-cross Abstract: As conversational AI systems become a larger part of the media landscape, they raise questions about whose interests they serve and the risks
arXiv:2607.10745v2 Announce Type: replace Abstract: This paper presents the first ChineseBabyLM Challenge, organized as part of NLPCC 2026. The challenge asked participants to train language models fr
arXiv:2510.10813v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to domains that require reasoning about other agents' behavior, such as negotiation, policy de
arXiv:2608.14588v1 Announce Type: new Abstract: Sequential multi-agent LLM pipelines chain specialized agents without verification at handoffs, creating a structural flaw with measurable and severe co
arXiv:2608.15971v1 Announce Type: cross Abstract: Dual-encoder models such as CLIP score an image-caption pair by a single inner product of two independently computed unit vectors, and fail at binding
arXiv:2608.15394v1 Announce Type: new Abstract: Human perception of time is subjective. Well-documented temporal illusions show that the brain relies on context and relational cues for judging duratio
arXiv:2607.18237v2 Announce Type: replace Abstract: Human visual similarity judgments are context-dependent. For example, two images may be similar in shape but distinct in color. Existing perceptual
arXiv:2608.14756v1 Announce Type: cross Abstract: Real-world EV charging data exhibit three interlocking pathologies: hardware fragmentation (network timeouts and billing resets split sessions), physi
arXiv:2608.15940v1 Announce Type: new Abstract: Modern encoder-decoder systems can produce fluent text even when their input contains no recoverable message. We study this failure in ASR and NMT throu
arXiv:2608.14913v1 Announce Type: cross Abstract: We introduce the Open-Strategy Dictator Game (OSDG), a variant of the classic dictator game in which each player's strategy is a natural-language docu
arXiv:2608.15337v1 Announce Type: cross Abstract: We disprove the expectation stated by Xin, Yu, and Ronney that the physical positive part strain G-equation should possess an effective burning veloci
arXiv:2505.04171v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the wor
arXiv:2608.15188v1 Announce Type: cross Abstract: We evaluate the quality of Claude AI-written Python tests against human-written Python tests from two established open-source projects Django and Pand
arXiv:2608.14691v1 Announce Type: new Abstract: Sequence models are conventionally distinguished by their backbone, the mechanism that routes information across positions, such as attention or recurre
arXiv:2608.14838v1 Announce Type: cross Abstract: Retrieval components for code assistants are tuned against retrieval metrics: a configuration that raises recall@k is adopted, and downstream task suc
arXiv:2608.16146v1 Announce Type: new Abstract: Deformable image registration models implicitly encode deformation priors through their parametrization and optimization. In this work, we conduct a val
arXiv:2603.00801v2 Announce Type: replace Abstract: Language agents increasingly act as web-enabled systems that search, browse, and synthesize information from diverse sources. However, these sources
arXiv:2608.16245v1 Announce Type: new Abstract: Disentangled representation learning seeks latent representations whose indicidual dimensions each align with a distinct covariate. Unsupervised approac
arXiv:2608.14558v1 Announce Type: new Abstract: Current multimodal models have demonstrated remarkable proficiency in recognizing static visual and auditory content. However, their capacity for abstra
arXiv:2608.16438v1 Announce Type: new Abstract: In a world where valuable artifacts are increasingly created, completed, or processed by LLMs, the central economic question is not only what the LLM ca
arXiv:2608.16630v1 Announce Type: cross Abstract: Repository-scale coding requires an agent to keep tests, imports, configuration, and migration rules consistent within a bounded context window. We mo
arXiv:2608.15687v1 Announce Type: new Abstract: Sycophancy, the tendency of a language model to change its answer to match a user's stated belief, is a common alignment failure. Existing activation st
arXiv:2608.16394v1 Announce Type: new Abstract: Generating regulation-compliant test scenarios is essential for validating safety-critical automotive systems, yet Large Language Models (LLMs) struggle
arXiv:2502.13207v4 Announce Type: replace-cross Abstract: Despite the increasing use of large language models for creative tasks, their outputs often lack diversity. Common solutions, such as sampling
arXiv:2603.06697v2 Announce Type: replace-cross Abstract: Vision--language models (VLMs) process images as visual tokens, yet their intermediate reasoning is often carried out in text, which can be su
arXiv:2608.16642v1 Announce Type: new Abstract: Accurate throwing of the American football requires precise regulation of release conditions, where coupled linear and angular momentum determine flight
arXiv:2405.17678v2 Announce Type: replace-cross Abstract: Achieving zero-shot adversarial robustness without sacrificing generalization remains challenging for foundation models such as CLIP, especial
arXiv:2608.15270v1 Announce Type: new Abstract: Miss a filing deadline by one day and the claim is barred, however strong the case. Computing that deadline is rarely simple: the period runs from a tri
arXiv:2608.16833v1 Announce Type: new Abstract: Ship fuel consumption (SFC) prediction supports vessel operation optimisation, emissions estimation, and decision support systems (DSS) for sustainable
arXiv:2510.12453v3 Announce Type: replace Abstract: Diffusion models excel in noise-to-data generation tasks, providing a mapping from a Gaussian distribution to a more complex data distribution. Howe
arXiv:2608.16443v1 Announce Type: new Abstract: Neurosymbolic (NeSy) Artificial Intelligence aims to integrate Deep Learning (DL) architectures with symbolic reasoning. While initial NeSy approaches h
arXiv:2608.15767v1 Announce Type: cross Abstract: We introduce TinyCast, an attention-free zero-shot forecaster that emits a predictive distribution from 146,505 parameters, on the premise that at thi
arXiv:2608.15297v1 Announce Type: new Abstract: Real-time 6DoF object pose estimation on resource-constrained hardware remains challenging, as accurate correspondence-based and refinement pipelines ty
arXiv:2608.16100v1 Announce Type: new Abstract: Generative image semantic communication converts an image into a text description and then performs text-to-image reconstruction at the receiver via dif
arXiv:2608.15935v1 Announce Type: new Abstract: Jointly fine-tuning an LLM on meeting-summarisation corpora of widely varying size raises a question that prior work leaves confounded: when a domain-ba
arXiv:2608.16122v1 Announce Type: cross Abstract: Adolescent Idiopathic Scoliosis (AIS) is a prevalent spinal deformity in adolescents that, if left untreated, can result in severe health outcomes. Tr
arXiv:2608.16775v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed in cybersecurity operations to assist cybersecurity analysts with rapid decision-making a
arXiv:2608.15736v1 Announce Type: new Abstract: Foundation models (FMs) increasingly support multimodal and geospatial reasoning, yet it remains unclear whether cartographic principles designed for hu
arXiv:2608.16643v1 Announce Type: cross Abstract: Automated detection of errors in clinical documentation is a promising application of large language models (LLMs), yet decisions to deploy such model
arXiv:2608.15996v1 Announce Type: new Abstract: We study second-order path-length regret in adversarial K-armed bandits against oblivious loss sequences. Bubeck et al. [2019] designed an algorithm tha