Knowledge catalogue
arXiv:2602.14466v2 Announce Type: replace Abstract: With natural language generation becoming a popular use case for language models, the Bias Benchmark for Question-Answering (BBQ) has grown to be an
arXiv:2604.16270v1 Announce Type: cross Abstract: The complexity of Vietnam's legal texts presents a significant barrier to public access to justice. While Large Language Models offer a promising solu
arXiv:2604.15805v1 Announce Type: cross Abstract: Learning robust robot policies in real-world environments requires diverse data augmentation, yet scaling real-world data collection is costly due to
arXiv:2409.17596v2 Announce Type: replace-cross Abstract: In recent years, live video streaming has gained widespread popularity across various social media platforms. Quality of experience (QoE), whi
arXiv:2604.14552v1 Announce Type: cross Abstract: Modern datacenters increasingly rely on low-power, single-slot inference accelerators to balance performance, energy efficiency, and rack density cons
arXiv:2603.29254v2 Announce Type: replace Abstract: Robotic grasping from single-view observations remains a critical challenge in manipulation. However, existing methods still struggle to generate re
arXiv:2604.13055v1 Announce Type: new Abstract: Today's evolving labor markets rely increasingly on recommender systems for hiring, talent management, and workforce analytics, with natural language pr
arXiv:2604.11419v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) analysts must answer complex questions over large collections of narrative security reports. Retrieval-augmented generat
arXiv:2604.11171v1 Announce Type: new Abstract: Computer-aided detection (CADe) of early neoplasia in Barrett's esophagus is a low-prevalence surveillance problem in which clinically relevant findings
arXiv:2603.02578v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive domains, yet their unpredictable behaviors, ranging from misalign
arXiv:2601.15671v2 Announce Type: replace-cross Abstract: Designing cycling infrastructure requires balancing the competing needs of diverse user groups, yet designers often struggle to anticipate how
arXiv:2604.07378v1 Announce Type: new Abstract: Autonomous vehicles in interactive traffic environments are often limited by the scarcity of safety-critical tail events in static datasets, which biase
arXiv:2604.07423v1 Announce Type: new Abstract: Physical Reservoir Computing (PRC) leverages the intrinsic nonlinear dynamics of physical substrates, mechanical, optical, spintronic, and beyond, as fi
AD2-Bench diagnoses multimodal reasoning via a Chain of Evidence, showing failures from spatial ambiguity and semantic uncertainty in adverse urban scenes.
arXiv:2610.21008v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) offers learned job selection for High-Performance Computing (HPC), but performance against heuristics alone does not e
arXiv:2610.21440v1 Announce Type: new Abstract: In automatic speech recognition (ASR), transcription errors with similar lexical or semantic discrepancies can have markedly different consequences for
arXiv:2610.15710v1 Announce Type: new Abstract: Long-term memory for assistants needs a gate that decides when a new utterance retires an old stored claim. Benchmark labels for this step mark a pair a
arXiv:2610.19387v1 Announce Type: new Abstract: Identification and ranking of salient propositions in documents is indirectly involved in many AI tasks, but few papers define proposition salience scor
arXiv:2610.15001v1 Announce Type: new Abstract: Multi-robot systems that combine the complementary capabilities of specialised platforms are critical for complex missions in challenging, inaccessible
arXiv:2610.13409v1 Announce Type: new Abstract: End-to-end planning in complex scenes must model diverse driving intentions and select the most appropriate trajectory using scene context and future ri
arXiv:2610.10604v1 Announce Type: cross Abstract: When generating verifiable code, natural language requirements are mapped to machine checked code using LLMs and agentic workflows. A crucial componen
arXiv:2610.05671v2 Announce Type: replace Abstract: Automatic prompt optimization (APO) has been widely employed to adapt large language models without updating their weights, yielding promising resul
arXiv:2610.11559v1 Announce Type: cross Abstract: Coding assistants such as Claude Code and Codex have become a major application of LLM agents, yet existing benchmarks remain far from real-world use,
arXiv:2610.07711v1 Announce Type: new Abstract: Accurate nuclei instance segmentation is essential for quantitative renal pathology, yet general-purpose models often struggle with low contrast, dense
arXiv:2610.04777v1 Announce Type: new Abstract: Inflammatory bowel disease (IBD) requires frequent imaging-based assessment, yet interpretation of modalities such as wireless capsule endoscopy (WCE) a
arXiv:2610.02561v1 Announce Type: new Abstract: Camera-based physiological monitoring can produce multiple estimates from several facial regions, extraction methods, and processing settings. Signal qu
arXiv:2610.00371v1 Announce Type: cross Abstract: Multi-agent systems derive their capabilities from sharing evidence, delegating tasks, and combining information across agents. The same process creat
arXiv:2610.00523v1 Announce Type: new Abstract: Conformal prediction guarantees marginal coverage, but a single calibration threshold can still spread that coverage unevenly, over-covering easy region
arXiv:2609.38684v1 Announce Type: new Abstract: Knowledge-intensive language-model systems typically represent external knowledge as text chunks or static graphs, with limited support for concept evol
arXiv:2609.39446v1 Announce Type: new Abstract: Existing full-duplex speech benchmarks cover only subsets of real-time interaction behaviors, often under limited contextual conditions. We introduce Du
arXiv:2609.39822v1 Announce Type: new Abstract: Vision-language-action (VLA) models face a timing gap between low-rate inference and high-rate robot execution. We characterize this gap through end-to-
arXiv:2609.36931v1 Announce Type: new Abstract: Reproducibility is essential for scientific research, yet prior work shows that LLM outputs vary with hardware and batching. We identify an overlooked f
arXiv:2609.37577v1 Announce Type: new Abstract: Large Language Model judges are widely used to rank texts and text-generating systems through pairwise comparison, and their reliability is typically as
arXiv:2609.38096v1 Announce Type: new Abstract: Policies with similar mean returns can differ sharply in rare failures, yet estimating lower-tail conditional value-at-risk (CVaR) accurately can requir
arXiv:2609.33449v1 Announce Type: new Abstract: Historical manuscript illustrations preserve rich visual evidence of past cultures. They depict people, animals, plants, diagrams, music notations, and
arXiv:2609.34683v1 Announce Type: new Abstract: The optimization of LLM serving engines, such as vLLM and SGLang, is largely benchmark-driven: optimizations, scheduling policies, hardware and system d
arXiv:2609.31985v1 Announce Type: new Abstract: Vision-language pretraining objectives differ in the spatial granularity of their supervision, yet the implications of this distribution for chest X-ray
arXiv:2609.34024v1 Announce Type: cross Abstract: Jev is a non-generative 'System One' model that assigns probabilities to predefined answer options and cannot answer outside them. Its accuracy and ca
arXiv:2609.34692v1 Announce Type: new Abstract: The reliable prediction of passenger train delays is a critical component of railway management. While contemporary research frequently attempts to maxi
arXiv:2609.33796v1 Announce Type: cross Abstract: Translating natural-language access-control requirements into policies requires careful reasoning about permissions, constraints, and exceptions, and
arXiv:2609.35686v1 Announce Type: new Abstract: Mechanistic interpretability (MI) aims to explain a model's behaviour through analyzing its internal computations; circuit-based explanations aim to iso
arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to interpret diverse natural language commands an
arXiv:2609.29551v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose LLM activations into sparse dictionary atoms, so that each distinct concept gets its own feature. One recurring beh
arXiv:2609.28567v1 Announce Type: new Abstract: Scanning electron microscopy (SEM) is routinely used to characterize the microstructural changes caused by hydrogen embrittlement (HE) in structural ste
arXiv:2609.26848v1 Announce Type: cross Abstract: Postoperative acute kidney injury (AKI) after major non-cardiac surgery carries substantial morbidity, yet early intraoperative risk stratification re
arXiv:2609.27650v1 Announce Type: new Abstract: Brain-to-language decoding translates neural activity associated with language production, internal speech and perception into linguistic or expressive
arXiv:2609.26860v1 Announce Type: cross Abstract: Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewa
arXiv:2609.26481v1 Announce Type: cross Abstract: Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simp
arXiv:2609.26489v1 Announce Type: new Abstract: Calibration of language models -- the alignment between expressed or implicit confidence and empirical correctness -- is a well-studied subfield within
arXiv:2609.26693v1 Announce Type: new Abstract: A coding agent must emit a valid tool call--a parseable invocation of a tool in the provided schema--before the harness can execute its chosen action. W
arXiv:2504.11582v3 Announce Type: replace Abstract: How can a monolingual English speaker determine whether an automatic translation in French is good enough to be shared? Existing MT error detection
arXiv:2609.22134v1 Announce Type: cross Abstract: Walsh-sequence-based receiver architectures offer an alternative approach for the reception and reconstruction of multiple simultaneous RF signals ove
arXiv:2609.23392v1 Announce Type: new Abstract: Underwater human--robot interaction requires gesture commands that are both easy for divers to use and reliable for robots to recognize. We investigate
arXiv:2609.21570v1 Announce Type: cross Abstract: Renewable energy communities (RECs) coordinate buildings, photovoltaic generation, batteries, electric vehicles and flexible loads. Controller studies
arXiv:2609.20875v1 Announce Type: cross Abstract: Parkinson's disease (PD) often manifests through speech impairments, facilitating accessible, non-invasive, and cost-effective severity assessment for
arXiv:2609.21457v1 Announce Type: new Abstract: Deep neural architectures are widely used for signal processing in automated pain assessment systems. However, architecture design has remained largely
arXiv:2603.02540v2 Announce Type: replace Abstract: Large language models (LLMs) display a unified 'general factor' of capability across 10 benchmarks (a finding confirmed by our factor analysis of 15
arXiv:2512.13142v5 Announce Type: replace Abstract: People use LLMs for reproductive-health questions, including abortion-related support. A response can sound supportive while answers reinforce harmf
arXiv:2609.19934v1 Announce Type: new Abstract: Depth-recurrent language models iteratively apply a small layer stack, decoupling per-token compute from distinct parameter count. To determine whether
arXiv:2609.19799v1 Announce Type: cross Abstract: LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run f