3,698 items tracked: 33 reported by two or more outlets, the rest by a single source. Most-corroborated first.
arXiv:2610.09848v1 Announce Type: cross Abstract: Inverse design in engineering often runs into a simple problem.
arXiv:2610.09891v1 Announce Type: cross Abstract: Human-Robot Collaboration (HRC) can facilitate mass customisation in Industry 4.0, with Reinforcement Learning from Human Feedback (RLHF) representing a promising approac…
arXiv:2610.09894v1 Announce Type: cross Abstract: In-database predictive query processing increasingly applies Transformer-based models within relational pipelines.
arXiv:2610.09906v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) for information technology and operational technology share one incident-response problem: a flood of correlated alerts and too few ana…
arXiv:2610.09914v1 Announce Type: cross Abstract: Reinforcement learning is crucial for improving large language models' reasoning and generalization.
arXiv:2610.09927v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models encode the entities and relations of a knowledge graph into a low-dimensional latent space, enabling tasks such as classification o…
arXiv:2610.09934v1 Announce Type: cross Abstract: We describe the Itgan systems for the three ASR subtasks of NADI 2026, namely robust country-level ASR (1.1), mixed-dialect ASR (1.2), and Tunisian code-switched ASR (1.3…
arXiv:2610.09938v1 Announce Type: cross Abstract: A holographic superconductor whose scalar mass depends on the gauge field strength, $M(\Fsq)$, reproduces a superconducting dome for a suitable $M$, and recovering that $…
arXiv:2610.10000v1 Announce Type: cross Abstract: Adversarial attacks on bandits aim to mislead a learner toward a target arm while keeping the attack cost small.
arXiv:2610.10061v1 Announce Type: cross Abstract: This paper presents TRACK (Telemetry-Based Racing Analysis and Coaching Kit), which is a framework for analyzing driving performance in sim racing and profiling how indiv…
arXiv:2610.10064v1 Announce Type: cross Abstract: AI is already writing a majority of code for frontier AI labs.
arXiv:2610.10066v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in both visual understanding and code generation.
arXiv:2610.10085v1 Announce Type: cross Abstract: Post-training tensor-network compression replaces Transformer linear layers with Tensor Train (TT) or Tree Tensor Network (TTN) operators, but standard decompositions min…
arXiv:2610.10091v1 Announce Type: cross Abstract: Knowledge-intensive tasks require answering many questions by reasoning about a shared corpus of artifacts (e.g., court cases, or scientific literature).
arXiv:2610.10170v1 Announce Type: cross Abstract: Retrieval-augmented generation systems increasingly rely on document-structure treatments: structure-aligned chunking, LLM-generated chunk contexts, heading-path metadata…
arXiv:2610.10182v1 Announce Type: cross Abstract: AI-generated faces can be difficult to distinguish from real ones, leaving viewers to rely on source labels when judging an image.
arXiv:2610.10183v1 Announce Type: cross Abstract: Long video understanding increasingly relies on external memory to organize massive visual streams into compact representations.
arXiv:2610.10227v1 Announce Type: cross Abstract: While Large Language Models (LLMs) possess rich world knowledge and impressive generalization capabilities, their direct application to tabular data classification is hin…
arXiv:2610.10232v1 Announce Type: cross Abstract: Large language models (LLMs) have already been shown to match or exceed human experts in persuasion.
arXiv:2610.10235v1 Announce Type: cross Abstract: Fluid antenna systems (FASs) offer significant spatial flexibility, yet securing them against eavesdropping is critical for practical FAS deployment in military, satellit…
arXiv:2610.10241v1 Announce Type: cross Abstract: AI could change which parts of science impede progress.
arXiv:2610.10246v1 Announce Type: cross Abstract: Constant-step stochastic approximation generally has a nonzero stationary mean error that persists under time averaging.
arXiv:2610.10250v1 Announce Type: cross Abstract: We study minimum-variance control of an unknown autoregressive system with exogenous inputs and coefficients that change at unknown times.
arXiv:2610.10266v1 Announce Type: cross Abstract: Dense self-expression matrices and full-affinity spectral clustering limit the scalability of subspace clustering.
arXiv:2610.10324v1 Announce Type: cross Abstract: Pretrained models for cell and nuclear instance segmentation differ substantially in architecture, pretraining data and objectives, parameter count, inference strategy, a…
arXiv:2610.10345v1 Announce Type: cross Abstract: Fine-tuning-as-a-service enables users to adapt aligned large language models (LLMs) to specialized tasks, but malicious fine-tuning can erode refusal behavior while pres…
arXiv:2610.10374v1 Announce Type: cross Abstract: A key challenge for multimodal large language models (MLLMs) is moving beyond visual recognition to constraint-aware cross-modal reasoning.
arXiv:2610.10455v2 Announce Type: replace-cross Abstract: Hallucinated information can propagate through multi-stage LLM systems and become part of the context for subsequent reasoning.
arXiv:2610.10463v1 Announce Type: cross Abstract: AI learning tools are rapidly entering classrooms, but evidence about whether they help students learn is mixed and rests mostly on test scores.
arXiv:2610.10536v1 Announce Type: cross Abstract: Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints.
arXiv:2610.10538v1 Announce Type: cross Abstract: As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later.
arXiv:2407.18994v2 Announce Type: replace Abstract: We consider the automatic online synthesis of black-box test cases from functional requirements specified as automata for reactive implementations.
arXiv:2601.14295v5 Announce Type: replace Abstract: Large language models increasingly function as artificial reasoners: they evaluate arguments, assign credibility, and express confidence.
arXiv:2603.11938v2 Announce Type: replace Abstract: Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must make many fine-grained, di…
arXiv:2603.18189v2 Announce Type: replace Abstract: Higher education instructors often lack timely and pedagogically grounded support, as scalable instructional guidance remains limited and existing tools rely on generic…
arXiv:2604.07652v2 Announce Type: replace Abstract: What-if analysis (WIA) lets users explore hypothetical scenarios by adjusting parameters, applying constraints, and scoping data through interactive interfaces.
arXiv:2604.08295v4 Announce Type: replace Abstract: As AI models grow more complex, explainability is essential for building trust, yet concept-based counterfactual methods still face a trade-off between expressivity and…
arXiv:2605.19376v3 Announce Type: replace Abstract: How should future neural reasoning systems implement extended computation?
arXiv:2605.25554v2 Announce Type: replace Abstract: As a core task in intelligent transportation systems, traffic forecasting plays a critical role in urban traffic management.
arXiv:2606.08849v2 Announce Type: replace Abstract: Urban public transport disruptions require rapid response strategies, yet existing studies rarely provide a decision support framework to compare alternative disruption…
arXiv:2606.22327v3 Announce Type: replace Abstract: The rapid growth of interactive Large Language Model serving has made efficient management of dynamic Key-Value cache footprints increasingly important for inference pe…
arXiv:2607.16421v2 Announce Type: replace Abstract: It has long been recognized that humans have the ability to switch between fast, reactive decision-making and slower, deliberative planning.
arXiv:2608.02287v2 Announce Type: replace Abstract: Agent skills have become an important mechanism for equipping language-model agents with reusable procedural knowledge.
arXiv:2608.29971v2 Announce Type: replace Abstract: As agentic systems evolve into complex multi agent orchestration workflows, there is a growing and critical need for systematic frameworks that measures an agent's beha…
arXiv:2609.00264v2 Announce Type: replace Abstract: Chain-of-thought monitoring is proposed for AI oversight, yet evaluations often provide monitors with a trusted reference answer.
arXiv:2609.03580v2 Announce Type: replace Abstract: The growing scale of academic peer review has motivated the use of Large Language Models (LLMs) as review assistants, yet LLMs can generate fluent but unsupported claim…
arXiv:2406.10741v2 Announce Type: replace-cross Abstract: The process of identifying human emotion and affective states from speech is known as speech emotion recognition (SER).
arXiv:2410.11687v4 Announce Type: replace-cross Abstract: In-context learning lets a sequence model adapt to a new task from examples in its input.
arXiv:2505.08854v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for…
arXiv:2505.12224v5 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have recently advanced robotic manipulation by translating natural-language instructions and visual observations into control…