arXiv:2511.04275v2 Announce Type: replace Abstract: Conformal prediction has emerged as a powerful framework for constructing distribution-free prediction sets with guaranteed coverage assuming only the exchangeability assumption.…
arXiv:2504.05349v5 Announce Type: replace Abstract: Network pruning is used to reduce inference latency and power consumption in large neural networks. However, most methods focus on empirical…
arXiv:2604.21334v2 Announce Type: replace Abstract: Do large language models (LLMs) exhibit systematic ideological bias when reasoning about economic causal effects? As LLMs are increasingly used in…
arXiv:2607.02087v2 Announce Type: replace Abstract: Hierarchical state-space models (HSSMs) offer a promising approach to long-horizon prediction by segmenting sequences into temporal chunks. However, their performance hinges…
arXiv:2607.10588v1 Announce Type: cross Abstract: Tasks such as customs tariff classification, export control categorization, and standards-based equipment coding require assigning an input instance to a fine-grained…
arXiv:2606.31715v2 Announce Type: replace-cross Abstract: Emerging uplink-dominant 6G use cases, such as cooperative vehicular streaming, require efficient transmission of high-volume visual data over limited wireless resources.…
arXiv:2607.09787v1 Announce Type: new Abstract: LiDAR semantic segmentation is a key perception task in autonomous driving, where false predictions can affect downstream planning and safety-critical decision-making.…
arXiv:2607.09683v1 Announce Type: new Abstract: This study systematically compares Turbo-Quant and SpectralQuant KV-cache compression, evaluating non-dominated schemes, including WHT rotation with Beta Lloyd-Max and QJL, through…
arXiv:2511.02584v2 Announce Type: replace-cross Abstract: Associative memory, traditionally modeled by Hopfield networks, enables the retrieval of previously stored patterns from partial or noisy cues. Yet, the…
arXiv:2607.10410v1 Announce Type: new Abstract: Reliable forecasting of several interrelated environmental variables - such as regional precipitation and temperature, or other correlated geophysical fields - across…
arXiv:2607.09817v1 Announce Type: cross Abstract: We propose a framework for the Markov chain (MC) choice model with panel data, including parameter estimation, personalized choice prediction, and…
arXiv:2607.09709v1 Announce Type: new Abstract: Post-training a code generator against a learned judge can optimize proxy features that raise the score without improving the artifact. We…
arXiv:2607.09740v1 Announce Type: new Abstract: Safe motion planning in advanced driver-assistance systems and autonomous vehicles requires an accurate understanding of how the surrounding traffic scene is…
arXiv:2607.10092v1 Announce Type: new Abstract: Spoken language models (SLMs) unify speech perception and reasoning, but adapting them to sensitive domains is underexplored, especially when the original…
arXiv:2607.11710v1 Announce Type: new Abstract: This paper addresses the problem of omnidirectional video interpolation, which plays an essential role in applications such as virtual reality and…
arXiv:2607.11839v1 Announce Type: new Abstract: This paper presents a cascaded Low-Rank Adaptation (LoRA)-based multimodal fusion framework for action and activity recognition in healthcare-oriented training environments. The…
arXiv:2607.09682v1 Announce Type: new Abstract: AI systems are increasingly used to assist consequential decisions in regulated domains such as auditing, finance, and healthcare. This creates a…
arXiv:2607.11821v1 Announce Type: cross Abstract: In multi-objective combinatorial optimization, unsupported non-dominated points typically outnumber supported points and are often significantly more challenging to compute. Recent studies…
arXiv:2508.00110v2 Announce Type: replace Abstract: Functional data present unique challenges for clustering due to their infinite-dimensional nature and potential sensitivity to outliers. An extension of the…
arXiv:2509.11146v2 Announce Type: replace Abstract: Magnitude, obtained as a special case of Euler characteristic of enriched category, represents a sense of the size of metric spaces…
arXiv:2607.11292v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed as conversational tutors, they risk institutionalizing systemic inequalities. This study presents a systematic…
arXiv:2510.11503v2 Announce Type: replace-cross Abstract: Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence (AI), often focusing on…
arXiv:2607.11052v1 Announce Type: cross Abstract: Machine learning progress is often attributed to scaling model size and dataset volume, yet the composition of data can be just…
arXiv:2607.09779v1 Announce Type: new Abstract: The deep nonnegative matrix factorization (DNMF) technique is proposed to address the low interpretability of deep learning-based methods in extracting multilayer…