Knowledge catalogue
arXiv:2610.11694v1 Announce Type: cross Abstract: Existing reaction models primarily learn molecular transformations, whereas enzy- matic reactions depend jointly on molecular structure and catalytic
arXiv:2610.08966v2 Announce Type: replace Abstract: Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek det
arXiv:2610.12089v1 Announce Type: new Abstract: Long-horizon mobile manipulation requires a robot to navigate multi-room environments and execute a sequence of manipulation skills under a single natur
arXiv:2602.00811v2 Announce Type: replace Abstract: Current Multimodal Affective Computing (MAC) systems heavily rely on the completeness of multiple modalities to accurately understand human's affect
arXiv:2610.12409v1 Announce Type: new Abstract: Safety benchmarks typically report one overall score for a suite of datasets, each of which may target one or more safety-related attributes, so models
All anyone ever talks in this sub is about x new model having x benchmark scores and how well it can code. Or some new tech to increase t/s for qwen. So I wanted to go back to the roots of this sub an
arXiv:2610.10047v1 Announce Type: new Abstract: Product-centric advertisement video generation aims to create promotional videos that preserve fine-grained product identity while presenting selling po
I'm developing a benchmark for a low resource language and I don't want it to be leaked and used for training when it is being used to get predictions. For locally run models it shouldn't be a problem
arXiv:2510.01335v2 Announce Type: replace Abstract: The manifold hypothesis suggests that data lies on manifolds with smaller intrinsic dimension (ID) than their ambient dimension. However there is no
arXiv:2610.10125v1 Announce Type: cross Abstract: Household robots need to continually navigate to different objects in the same environment, many of which are small and portable, such as tools and to
arXiv:2610.06988v1 Announce Type: new Abstract: Knowledge tracing (KT) models are predominantly evaluated using aggregate metrics such as area under the curve (AUC) and accuracy. However, these global
arXiv:2610.07232v1 Announce Type: new Abstract: Accurate short-term load forecasting (STLF) is essential for the reliable and efficient operation of modern power systems. While time series foundation
arXiv:2610.07616v1 Announce Type: new Abstract: We present a repertoire-free benchmark for soft-robot damage recovery under nine online trials. The protocol pairs damage masks within each morphology,
arXiv:2610.07026v1 Announce Type: new Abstract: The Offline AI Modules workstream enables practical, low-power, and community-accessible deployment of voice-first AI systems that operate fully offline
arXiv:2610.08684v1 Announce Type: new Abstract: Modern video models can generate realistic videos from real appearance references and proxy renders that specify scene structure, viewpoint changes, and
arXiv:2610.08161v1 Announce Type: cross Abstract: Ambient documentation systems are rapidly gaining adoption, yet their impact on clinical note quality remains poorly characterized. We introduce MedCo
arXiv:2610.08733v1 Announce Type: new Abstract: Language models provide a plug-and-play interface between humans and robots, but important challenges remain when speech, dialogue, fast interaction, an
arXiv:2610.07802v1 Announce Type: new Abstract: Bird monitoring in natural environments is challenging due to the small size of some species of birds relative to the scene, background clutter, variabi
arXiv:2406.12150v2 Announce Type: replace Abstract: Post-hoc attribution is widely used to identify important model inputs, but evaluating whether these attributions identify truly informative feature
arXiv:2610.04558v1 Announce Type: cross Abstract: We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in project
Introducing GeoGuess Bench! A benchmark to measure how good AI models are at playing GeoGuessr. We gave each model 210 photos from around the world, asked it to predict where each photo was taken, and
Introducing Hermes Index: an average of benchmarks measuring model performance in Hermes Agent. Our goal with Hermes Index is to better inform users choosing between models and to show labs how they p
arXiv:2610.06469v1 Announce Type: new Abstract: Closed-loop evaluation of end-to-end driving requires continuous rollouts that reveal how earlier decisions affect subsequent driving. However, existing
arXiv:2610.06121v1 Announce Type: new Abstract: Adverse weather and poor illumination remain major challenges for robust ego-trajectory planning in mobile autonomy. 4D radar offers reliable sensing un
We've been building a benchmark out of real concurrency bugs (race conditions, deadlocks, cancellation issues) taken from merged PRs in about 100 Python projects. Each task gets graded by the project'
arXiv:2610.04432v1 Announce Type: new Abstract: Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manu
arXiv:2610.03639v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support legal practice, education, and research, yet their reliability in national legal systems o
arXiv:2610.03524v1 Announce Type: new Abstract: General-purpose Text-to-SQL systems achieve strong performance on academic benchmarks like Spider and BIRD, where schemas are relatively shallow and col
arXiv:2610.02293v1 Announce Type: new Abstract: HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of options and returns a pr
arXiv:2610.00353v1 Announce Type: new Abstract: A sound judgment applies the law to established facts and weighs the circumstances in which they arose. However, existing methods swing between rigid st
arXiv:2610.00531v1 Announce Type: new Abstract: AI-generated content, often called AI slop, is increasingly common everywhere, particularly in academia. Slop in AI-generated scientific papers, however
arXiv:2610.01499v1 Announce Type: new Abstract: Recent video generation models can produce highly realistic videos from natural language instructions, with visual quality approaching cinematic standar
arXiv:2609.39371v1 Announce Type: new Abstract: In hospital workflows, electronic health records (EHRs) are often noisy, and may not contain the evidence needed to confirm events or measurements refer
arXiv:2609.39777v1 Announce Type: new Abstract: LLM-based multi-agent systems coordinate specialized reasoning through aggregation, interaction, and adaptive control, yet their potential for graph lea
arXiv:2511.00421v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise in medical applications, but their ability to detect and correct errors in clinical texts remains un
arXiv:2609.39673v1 Announce Type: new Abstract: Can a pretrained graph model replace training and tuning a separate predictor for each dataset? Answering this requires evaluating prediction quality al
Hybrid search, reranking, query decomposition, and query expansion are often treated as must-haves for good RAG. We wanted to see how much each actually helped, so we tested them. Same model, same emb
arXiv:2607.11849v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on high-school and competition-level mathematics, yet their capabilities on advanc
arXiv:2609.35820v1 Announce Type: cross Abstract: English-only benchmarks expose only a narrow slice of voice-agent behavior. We introduce au-Multilingual, extending au-Voice to Spanish, Brazilian Por
arXiv:2609.36492v1 Announce Type: cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse dete
arXiv:2609.32192v2 Announce Type: replace Abstract: Multi-agent workflows require task-relevant information to be shared across agents, while irrelevant, stale, unverified, or incompatible information
arXiv:2609.37658v1 Announce Type: new Abstract: LLM agents are increasingly expected to support enterprise workflows, where tasks often involve missing information, uncertainty, feedback, and long-ter
arXiv:2609.32890v1 Announce Type: new Abstract: Language models are increasingly evaluated as vulnerability detectors, and scores reported for similar models differ widely between papers. We measured
arXiv:2609.34782v1 Announce Type: cross Abstract: Many physical tasks in human environments require collaboration, from assisting a partner to jointly manipulating an object. Yet, existing humanoid be
arXiv:2609.31632v1 Announce Type: new Abstract: Electroencephalography (EEG) analysis is evolving from short-segment classification toward long-horizon interpretation that demands iterative evidence a
arXiv:2609.31648v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are studied mainly in robotics, where visual observations and language instructions are mapped to physical actions.
arXiv:2609.32352v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown increasing potential for medical image understanding, yet their capabilities in ophthalmic imaging remain insuf
arXiv:2609.33158v1 Announce Type: new Abstract: Progress in AI-based retinal image analysis has advanced with foundation models, yet evaluating their reliability remains challenging. Performance repor
arXiv:2609.33812v1 Announce Type: cross Abstract: Repeated runs of the same coding agent are known to give different benchmark scores. We ask what that variation means for a team running an agent on i
arXiv:2609.32813v1 Announce Type: new Abstract: Large vision-language models (VLMs) have emerged as a powerful paradigm for urban and spatial AI. However, current state-of-the-art large VLMs still str
arXiv:2609.34480v1 Announce Type: new Abstract: Reliable visual question answering requires correct answers when evidence is sufficient and abstention when it is not. We introduce a benchmark that con
arXiv:2609.31306v1 Announce Type: new Abstract: Tabular in-context learners such as TabPFN, Mitra, or ConTextTab rely on alternating row and column attention over 2D sequences of latent embeddings. Th
arXiv:2609.31587v1 Announce Type: cross Abstract: We investigate whether natural-language documentation helps coding agents resolve software issues, and we build the tools to construct and evaluate it
arXiv:2609.31468v1 Announce Type: cross Abstract: LLMs increasingly act as purchasing agents, which makes the LLM, not the user, the one choosing among the options that satisfy a request; its preferen
arXiv:2609.28813v1 Announce Type: new Abstract: Cinematography, the craft of visual storytelling through framing, lighting, and camera operation, fundamentally shapes how audiences perceive and emotio
arXiv:2603.18612v2 Announce Type: replace Abstract: We introduce DiscoPhon, a multilingual benchmark for evaluating unsupervised phoneme discovery from discrete speech units. DiscoPhon covers 6 dev an
arXiv:2609.28876v1 Announce Type: new Abstract: We introduce Forecast-Dojo, a replayable environment for benchmarking and training LLM forecasting agents. It combines resolved prediction-market questi
Thariq (@trq212) posted on September 25 , 2026 that readers can view interactive explainers of benchmarks and demos he built on the new Claude dev site (https://claude.dev/blog). The tweet includes a
arXiv:2609.29028v1 Announce Type: new Abstract: In this paper, we propose RGBD20K, a novel dataset for facilitating the development of more robust and general RGB-D semantic segmentation by encompassi
arXiv:2609.29445v1 Announce Type: new Abstract: We audit a multilingual affective generation benchmark eight instruction-tuned LLMs producing emoji summaries for 17,100 Bangla, English and Hindi sente