All entries

Can LLM design high-quality experiments? A Comprehensive and Systematic Benchmark on Autonomous Experimental Design

arXiv:2608.03501v1 Announce Type: new Abstract: AI for Research (AI4Research) leverages AI to automate and improve scientific workflows. While experimental design is a critical stage of the research p

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Can LLMs Test Terminal User Interfaces?

DGX agent

arXiv:2608.03743v1 Announce Type: cross Abstract: Terminal User Interfaces (TUIs) combine the stateful, screen-oriented behaviour of GUIs with terminal deployment and are now common in developer tools

model-releasesarxiv-cs-ai

5 Aug 2026

Can Text-to-Image Models Draw from the Right Frame of Reference?

model-releasesarxiv-cs-cv

arXiv:2608.03357v1 Announce Type: new Abstract: Spatial instruction following has become a crucial requirement for text-to-image (T2I) generation. A common challenge arises when directional expression

Can Training Logs Make Model Comparisons More Precise?

arXiv:2608.02705v1 Announce Type: cross Abstract: Comparing stochastically trained models requires estimating both a performance difference and its uncertainty from repeated runs. We study whether tra

CAPE-T2V: Captioner-Anchored Prompt Enhancement toward Two-Sided Conditioning Alignment in Text-to-Video Generation

arXiv:2608.03046v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion transformers (DiTs) are trained with detailed video captions, whereas inference often relies on user prompts rewritten by

CARE-Bench: Benchmarking Patient-Facing LLM Triage

arXiv:2608.03731v1 Announce Type: new Abstract: Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the

Local Ai

CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement

arXiv:2608.03890v1 Announce Type: cross Abstract: A clinically useful chest X-ray system must go beyond fluent report generation: it should classify findings with tunable decision thresholds, localize

local-aiarxiv-cs-ai

Agents

CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting

arXiv:2608.03031v1 Announce Type: new Abstract: Time series forecasting is fundamental to decision-making in complex systems, where future dynamics are influenced not only by historical observations b

agentsarxiv-cs-ai

Tutorials

Causal Inference with Unstructured Outcomes

arXiv:2608.03085v1 Announce Type: cross Abstract: Causal inference has traditionally centered on scalar outcomes: whether a patient recovers, how much a worker earns, or how many visits a website rece

tutorialsarxiv-cs-lg

CausalOPD: First-Wrong-Step Supervision for Distilling Causal Chain Reasoning

arXiv:2608.03673v1 Announce Type: new Abstract: Many critical reasoning tasks, including clinical diagnosis, legal judgment, and industrial fault diagnosis, require step-dependent causal chains in whi

safetyarxiv-cs-lg

Caved or Convinced: Temporal Sampling Gates Claim Deference in Video Large Language Models

arXiv:2608.03160v1 Announce Type: cross Abstract: When asked which of two events came first, video large language models can fail in two opposite ways: cave to a false claim, or reject a true one. Pri

Channel-wise Dynamic Knowledge Distillation via Adaptive Sample Generation for Action Recognition

arXiv:2608.03100v1 Announce Type: new Abstract: Knowledge Distillation (KD) offers a promising yet underexplored path for compressing large action recognition models. However, existing KD methods suff

Character Iconicity vs. Arbitrariness: An Arabic NLP Perspective

arXiv:2608.02935v1 Announce Type: new Abstract: Arabic script uses 28 letters, many of which share a common base shape (rasm) and are distinguished only by dot placement. Because early Arabic manuscri

researcharxiv-cs-cl

ChartAnno: Evaluating MLLMs for Chart Annotation Generation

arXiv:2608.03464v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in chart understanding, generation, and editing, but their ability to annotate e

Chat Debugging: An Exploratory Study of Human-AI Collaboration to Debug Analog Circuits

arXiv:2608.02955v1 Announce Type: cross Abstract: This research paper describes an exploratory study on the effectiveness of Chat Debugging: troubleshooting malfunctioning analog circuits on breadboar

ChiEngMixBench: Evaluating Large Language Models on Expert-Style Chinese-English Terminology Mixing

arXiv:2601.16217v2 Announce Type: replace-cross Abstract: Large language models increasingly mediate multilingual professional communication, where useful generation requires adapting to community con

ChronoLens: Measuring Language Change Across Time, Languages, and Linguistic Levels

arXiv:2608.03507v1 Announce Type: cross Abstract: Historical language change affects morphology, syntax, semantics, and pragmatics, yet computational studies typically examine these levels with incomp

Local Ai

CIGTSurv: Clinical Information Guided Tri-modal Survival Prediction with Local Prototype Association and Global Feature Alignment

arXiv:2608.03247v1 Announce Type: cross Abstract: Multimodal learning has significantly advanced survival prediction by integrating pathology images with genomic data. However, clinical information, d

local-aiarxiv-cs-cl

Clarity Contrast and Similarity Selection for Multi-Focus Image Fusion

arXiv:2608.03252v1 Announce Type: new Abstract: Multi-focus image fusion (MFIF) aims to generate an all-in-focus image from multiple images of the same scene focused at different regions. Most existin

Clinically-Grounded Hierarchical Classification for Consistent Chest X-ray Interpretation

arXiv:2608.03016v1 Announce Type: new Abstract: Accurate chest X-ray interpretation is inherently hierarchical. Clinical decisions depend not only on what abnormality is present but where it is situat

CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification

arXiv:2403.09281v3 Announce Type: cross Abstract: We propose CLIP-EBC, the first fully CLIP-based model for accurate crowd density estimation. While the CLIP model has demonstrated remarkable success

CLIP4VI-ReID: Learning Modality-shared Representations via CLIP Semantic Bridge for Visible-Infrared Person Re-identification

arXiv:2511.10309v2 Announce Type: replace Abstract: This paper proposes a novel CLIP-driven modality-shared representation learning network named CLIP4VI-ReID for VI-ReID task, which consists of Text

Compass: Degradation-Simulated Reciprocal Learning with Lightweight Needle RWKV for Multimodal Crack Segmentation under Missing Modalities

arXiv:2608.03559v1 Announce Type: new Abstract: In multimodal crack segmentation for industrial facilities, the key challenge is preventing missing modalities from degrading pixel-level performance wh

Hardware

Compound and Parallel Modes of Tropical Convolutional Neural Networks

arXiv:2504.06881v2 Announce Type: replace-cross Abstract: Convolutional neural networks (CNNs) are foundational to many state-of-the-art computer vision systems, yet their reliance on multiplication-i

hardwarearxiv-cs-ai

Computing Actual Causes for Neural Network Predictions under Structured Causal Inputs

arXiv:2608.03772v1 Announce Type: new Abstract: Explaining the predictions of neural networks is a central challenge in trustworthy AI. Existing explanation methods, such as those based on feature att

applicationsarxiv-cs-ai

Conditionally Identifiable Latent-Environment Modeling for Out-of-Distribution Recommendation

arXiv:2608.03647v1 Announce Type: cross Abstract: Out-of-distribution (OOD) recommendation is vulnerable to preference shifts induced by a latent environment. Existing methods can infer latent states

researcharxiv-cs-lg

Confident but Unreliable: A Behavioral Safety Audit of Vision-Language Models on Brain MRI

model-releasesarxiv-cs-cv

arXiv:2608.02790v1 Announce Type: new Abstract: Vision-language models (VLMs), including medical specialists, are increasingly proposed for medical imaging, yet their stated confidence is rarely evalu

Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models

arXiv:2608.03360v1 Announce Type: cross Abstract: Non-intrusive reduced-order models (NIROMs) have become a standard tool for approximating parametric partial differential equations from computer desi

ConformalShift: Targeted Event Reordering Against Adaptive ECG Monitoring

arXiv:2608.03628v1 Announce Type: new Abstract: Adaptive conformal prediction can recover clinically important heartbeat classes missed by a point classifier, but delayed feedback makes its decisions

ConlangBench: Exploring Language Knowledge and Learning in LLMs through Diverse Constructed Languages

model-releasesarxiv-cs-cl

arXiv:2608.03505v1 Announce Type: new Abstract: Constructed languages (conlangs) are intentionally created human languages with a rich tradition of linguistic creativity. Despite their potential for s

Consensus Measures for Unstructured Biomedical Text Annotations

arXiv:2608.03529v1 Announce Type: new Abstract: Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer. Because the target concepts are not known in ad

researcharxiv-cs-cl

Agents

Contact-Driven Localization in a Freeform Robotic Self-Assembled Structure

arXiv:2608.02895v1 Announce Type: new Abstract: Accurate localization remains a key challenge in swarm robotics, particularly for self-reconfigurable systems that must identify relative positions to f

agentsarxiv-cs-ro

Agents

ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?

arXiv:2608.03874v1 Announce Type: new Abstract: Modern agent frameworks equip large language models with external skill libraries to solve complex tasks. However, it remains unclear whether these syst

agentsarxiv-cs-ai

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution

arXiv:2608.03483v1 Announce Type: cross Abstract: Existing chunk-based Vision-Language-Action (VLA) models execute a fixed number of actions (i.e., execution horizon) before replanning, turning replan

safetyarxiv-cs-ai

Contrast-invariant deep ptychography neural networks

arXiv:2608.02869v1 Announce Type: new Abstract: Ptychography neural networks suffer from scaling inconsistencies when generalizing out of distribution, limiting their real world viability. We address

Control Barrier Functions via Minkowski Operations for Safe Navigation among Polytopes

arXiv:2608.02886v1 Announce Type: new Abstract: Safely navigating polytopic environments while respecting the dynamics, control, and exact geometry of the underlying system is a challenge in robotics.

safetyarxiv-cs-ro

Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size

arXiv:2404.05185v4 Announce Type: replace-cross Abstract: This paper deals with a class of neural SDEs and studies the limiting behavior of the associated sampled optimal control problems as the sampl

researcharxiv-cs-lg

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL

arXiv:2608.03108v1 Announce Type: cross Abstract: Offline reinforcement learning (offline RL) can benefit from nearby out-of-distribution (OOD) actions, but estimation errors at these actions may be a

researcharxiv-cs-cl

CorePath: A Breast-Specialized Pathology Foundation Model for Core Needle Biopsy Diagnosis and Risk-Controlled Report Generation

arXiv:2608.03079v1 Announce Type: cross Abstract: Breast core needle biopsy (CNB) is central to breast cancer diagnosis yet remains challenging because limited tissue sampling, lesion heterogeneity, a

CPrefix: A Combinatorial Tensor Framework for Structured Discrete Color Mappings

arXiv:2608.03863v1 Announce Type: new Abstract: Discrete multi-channel mappings are typically represented through sampled values, providing accurate evaluations but limited insight into their underlyi

Crayotter: Learning Long-Horizon Video Editing Agents via Group-Relative Preference Backpropagation

arXiv:2608.02694v1 Announce Type: new Abstract: Long-horizon video editing agents receive final-product feedback only after many interdependent decisions. Yet editing quality is subjective, admits mul

applicationsarxiv-cs-cl

Tutorials

CRIL-U-Net: Compact Ratio-Interaction Learning for Focal Cortical Dysplasia Segmentation from T1w and FLAIR MRI

arXiv:2608.03185v1 Announce Type: new Abstract: Focal cortical dysplasia (FCD) type II is an important structural cause of drug-resistant focal epilepsy, but its small size, heterogeneous appearance,

tutorialsarxiv-cs-cv

Cross-Anesthetic ECoG State Decoding Fails at the Decision Threshold, Not the Representation

arXiv:2608.02646v1 Announce Type: cross Abstract: Decoders of anesthetic state from cortical activity fail across drug classes, most notoriously ketamine, but reported accuracy cannot say whether the

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation

arXiv:2608.03147v1 Announce Type: new Abstract: Referring Remote Sensing Image Segmentation (RRSIS) has achieved significant progress through the integration of VLMs and the Segment Anything Model (SA

Cross-Country Learning for National Infectious Disease Forecasting Using European Data

arXiv:2601.20771v2 Announce Type: replace-cross Abstract: Accurate forecasting of infectious disease incidence is critical for public health planning and timely intervention. While most data-driven fo

Cross-Layer Interaction under Weight-Space Ablation: A Closed-Form Attention Jacobian Bound and a Test on a Real Pretrained Model

arXiv:2608.03629v1 Announce Type: new Abstract: A companion paper studies when activation patching and weight-space ablation agree, inside an idealized model where a conditional computation is carried

Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili

model-releasesarxiv-cs-cl

arXiv:2608.03532v1 Announce Type: new Abstract: Large language models are increasingly deployed in multilingual contexts, yet safety alignment and bias evaluation remain overwhelmingly English-centric

Cross-Model KV Cache Transfer in LLM Families: A Closed-Form Linear Mapping for Prefill Reuse

arXiv:2608.03893v1 Announce Type: new Abstract: Production deployments often swap between different-sized models in a family for cost-quality cascading, mid-conversation switching, and routing, and ea