All entries

TADPO: Reinforcement Learning Goes Off-road

arXiv:2603.05995v2 Announce Type: replace-cross Abstract: Off-road autonomous driving poses significant challenges such as navigating unmapped, variable terrain with uncertain and diverse dynamics. Ad

TAKE: Trajectory-Aware Knowledge Estimation for Text Dataset Distillation

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2607.11898v1 Announce Type: new Abstract: Large-scale text corpora have become a quiet bottleneck in modern NLP, not just in storage, but in the accumulated cost of training, fine-tuning, and co

researcharxiv-cs-cl

15 Jul 2026

TerraLogic: A Benchmark for Hierarchical Geospatial Reasoning in Earth Observation

model-releasesarxiv-cs-cv

arXiv:2607.12497v1 Announce Type: new Abstract: Beyond perception, reasoning is essential in remote sensing for advanced interpretation, inference, and decision-making. Recent advances in large langua

TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scale

arXiv:2607.13028v1 Announce Type: cross Abstract: Training robust autonomous driving agents requires a simulator that is fast enough for reinforcement learning at scale, realistic enough to ground beh

Text-Aided Multi-Modal Panoptic Symbol Spotting for CAD Floor Plan Drawings

arXiv:2607.12678v1 Announce Type: cross Abstract: Computer-Aided Design (CAD) floor plan drawings contain both graphical primitives and textual annotations, which provide complementary geometric and s

The Benjamini--Hochberg Procedure Can Fail to Control the FDR for Correlated Two-Sided Gaussian Tests

arXiv:2607.12208v1 Announce Type: cross Abstract: We show that the Benjamini--Hochberg procedure can fail to control the false discovery rate (FDR) at its nominal level for correlated two-sided Gaussi

The Capacity of Thought: Benchmarking Llama 3.2 in Semantic fMRI Neural Language Decoding and Improving the Huth Encoding-Model Baseline

arXiv:2607.12079v1 Announce Type: new Abstract: Decoding continuous language from fMRI signals remains a core challenge in non-invasive brain-computer interface research. We present two complementary

The Computational Basis of Confidence in Large Language Models

arXiv:2607.12447v1 Announce Type: cross Abstract: Reliable confidence -- the probability that a model's own answer is correct -- is essential for the trustworthy deployment of language models. Existin

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

agentsarxiv-cs-ai

The Geometry of Memorization: Finite-Time Spectral Sensitivity as a Diagnostic for Flow Matching Models

arXiv:2607.12616v1 Announce Type: new Abstract: Continuous-time generative frameworks construct probability paths between base and target domains by optimizing time-dependent velocity fields. While th

The GEST-Engine: From Event Graphs to Synthetic Video. A Full Technical Report

arXiv:2607.12231v1 Announce Type: new Abstract: We present the GEST-Engine, a complete system that goes from natural-language text to fully-annotated multi-actor video. At its core is an explicit worl

agentsarxiv-cs-cv

The Illusion of Robustness: Aggregate Accuracy Hides Prediction Flips under Task-Irrelevant Context

arXiv:2607.12963v1 Announce Type: new Abstract: As large language models (LLMs) grow more capable, they are increasingly deployed in context-rich settings where task inputs are often accompanied by lo

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

arXiv:2405.11667v2 Announce Type: replace Abstract: Local SGD is a popular optimization method in distributed learning, often outperforming other algorithms in practice, including mini-batch SGD. Desp

The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank

arXiv:2607.12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human see

The One-Word Census: Answer-Choice Conformity Across 44 Language Models

arXiv:2607.12796v1 Announce Type: cross Abstract: When a language model must pick one answer from a large space of equally valid options, which does it pick -- and how often is it the same answer ever

The Seriality Gap in Video Diffusion Models

arXiv:2607.13031v1 Announce Type: cross Abstract: When one ball strikes another, then another, video models should predict the consequences of each bounce. In controlled experiments on multi-ball hard

The Sound of Absence: Audio-Language Embedding Models Struggle with Negation

arXiv:2607.12290v1 Announce Type: cross Abstract: Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-o

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting

arXiv:2607.13006v1 Announce Type: new Abstract: A growing family of indices scores how predictable a series is from its spectrum. Practitioners increasingly read these scores as answering a different

The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

model-releasesarxiv-cs-cv

arXiv:2312.17670v5 Announce Type: replace Abstract: The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to

Thompson Sampling Is 2-Competitive for Mistakes

arXiv:2607.12389v1 Announce Type: cross Abstract: We consider Bayesian bandit models and prove that Thompson sampling makes at most twice the expected number of mistakes (selections of a suboptimal ar

safetyarxiv-cs-lg

Applications

Tilt-Ropter: A Fully Actuated Hybrid Aerial-Terrestrial Vehicle with Tilt Rotors and Passive Wheels

arXiv:2602.01700v3 Announce Type: replace Abstract: In this work, we present Tilt-Ropter, a fully actuated hybrid aerial-terrestrial vehicle (HATV) that integrates tilt rotors with passive wheels to e

applicationsarxiv-cs-ro

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis

arXiv:2511.18089v2 Announce Type: replace Abstract: Multimodal survival analysis aims to improve cancer prognosis using heterogeneous biomedical data, such as histopathology images and genomic profile

safetyarxiv-cs-cv

Token Reduction Is Not Cost Reduction

arXiv:2607.12161v1 Announce Type: new Abstract: Context-reduction layers for API-based coding agents, including command-output compressors, retrieval rankers, and payload-optimizing proxies, are usual

Toward Localizing and Repairing Bias in Transformer Attention Heads

arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

local-aiarxiv-cs-lg

Toward Metaphor-Fluid Conversation Design for Voice User Interfaces

arXiv:2502.11554v3 Announce Type: replace-cross Abstract: Metaphors play a critical role in shaping user experiences with Voice User Interfaces (VUIs), yet existing designs often rely on static, human

Toward Production-Ready Federated Learning in Healthcare: Privacy, Orchestration, and Governance in MLOps

arXiv:2607.10467v2 Announce Type: replace-cross Abstract: Healthcare organizations often cannot freely centralize patient data because medical records are sensitive, regulated, and institutionally con

local-aiarxiv-cs-lg

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

arXiv:2607.12113v1 Announce Type: cross Abstract: One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around fi

Towards Self-Evolving Agents: A Human-Inspired Adaptive Exploration-Exploitation Framework for Genetic Network Programming

arXiv:2607.11913v1 Announce Type: cross Abstract: Recent advancements in agentic AI have increasingly moved toward graph-based methods, driven by the demand for explainable, human-centered, and non-li

Towards Vision-Free CIR: Attribute-Augmented Scoring and LLM-Based Reranking for Zero-Shot Composed Image Retrieval

arXiv:2607.12621v1 Announce Type: new Abstract: Recent work has shown that 'Vision-Free'' approaches (representing images as text) can be effective for standard image retrieval tasks. However, it rema

TRACE: An Operational Reasoning Schema for Auditable Agentic Commitments

arXiv:2607.12480v1 Announce Type: new Abstract: This paper defines TRACE (Typed Reasoning And Commitment Evidence): a typed, versioned schema for recording reasoning traces, a reference procedure for

Traceback Translators Against Forgetting in Continual Fake Speech Detection

arXiv:2607.12569v1 Announce Type: cross Abstract: Fake speech detectors are increasingly challenged by the development of new and more accurate generative models. To cope with this problem, continual

Applications

TraceSynth: Generating Production-Quality Kernel Traces with Constraint-Guided Diffusion Models

arXiv:2607.12104v1 Announce Type: cross Abstract: Machine learning models for system diagnostics rely on kernel execution traces to capture fine-grained system behavior, but collecting production trac

applicationsarxiv-cs-lg

Tracing Agentic Failure from the Flow of Success

arXiv:2607.12747v1 Announce Type: new Abstract: Failure attribution for LLM-based agentic systems, i.e., identifying which steps in a failure trajectory caused the task to fail, is critical for debugg

agentsarxiv-cs-ai

Track, Rank, Crack: Epistemic Working Memory Scales Multi-Hop Reasoning in Language Agents

arXiv:2607.12267v1 Announce Type: cross Abstract: Language agents that interleave reasoning and tool use degrade sharply as reasoning chains lengthen, even when each individual step is easy. We trace

TRAIL: A Platform for Configurable Human--AI Teaming Experiments

arXiv:2607.12180v1 Announce Type: cross Abstract: An AI teammate's design properties (personality, communication style, when it speaks) can shape a team's trust, coordination, and decisions. Studying

Traj-VLN: Learning Pixel-Space Interaction via Autoregressive Trajectory Generation

arXiv:2607.10744v2 Announce Type: replace Abstract: Benefiting from the powerful priors embedded in large-scale pre-training data and the emerging commonsense reasoning ability, large language models

agentsarxiv-cs-cv

Transforming LLMs into Efficient Cross-Encoders via Knowledge Distillation for RAG Reranking

arXiv:2607.11933v1 Announce Type: new Abstract: Cross-encoders achieve high reranking accuracy in Retrieval-Augmented Generation (RAG) pipelines but impose quadratic inference costs that limit real-ti

Translation as a Computationally Efficient Bridge: Feasibility of English BERT for Low-Resource Languages

arXiv:2607.12612v1 Announce Type: new Abstract: BERT models have revolutionised Natural Language Processing (NLP) through their ability to process unstructured text across diverse domains. However, de

researcharxiv-cs-cl

TrustVLA: Mechanism-Guided Inference-Time Defense Against Vision-Language-Action Backdoors

arXiv:2607.12571v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are deployed through pipelines that end users cannot audit, and a poisoned VLA can behave normally on clean observat

safetyarxiv-cs-ro

TSCA-Net: Temporal-Spatial Clique Attention for Interpretable Multimodal Pedestrian Trajectory Prediction

arXiv:2607.11939v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction in crowded environments remains challenging due to the multimodal uncertainty of human motion and the variable

local-aiarxiv-cs-cv

Tutorials

UMSS: Towards Unsupervised Multi-modal Semantic Segmentation

arXiv:2607.12372v1 Announce Type: new Abstract: Multimodal semantic segmentation (MSS) is essential for robust perception in complex environments, yet its potential remains largely untapped because of

tutorialsarxiv-cs-cv

Uncertainty-Aware Multi-Source Retinal Fluid Segmentation in OCT

arXiv:2607.12212v1 Announce Type: cross Abstract: Measuring retinal fluid from optical coherence tomography (OCT) drives treatment decisions in macular disease, but manual annotation is slow and segme

Understanding Sources of Demographic Predictability in Brain MRI via Disentangling Anatomy and Contrast

arXiv:2603.04113v2 Announce Type: replace-cross Abstract: Demographic attributes can be predicted from medical images, raising concerns about bias in clinical AI systems. In X-ray imaging, acquisition

Understanding Structured Health Data through Interaction-Aware Mixture-of-Experts

arXiv:2607.12255v1 Announce Type: new Abstract: We study interaction-aware mixture-of-experts for post-stroke rigidity prediction using multi-level views of structured health records. Despite minimal

UniMedSeg: Unified In-Context Learning for Multi-Paradigm 2D/3D Medical Image Segmentation

arXiv:2607.12896v1 Announce Type: new Abstract: Medical image segmentation foundation models are expected to generalize across diverse clinical scenarios, yet existing universal methods remain fragmen

UniVR: Thinking in Visual Space for Unified Visual Reasoning

model-releasesarxiv-cs-cv

arXiv:2607.12800v1 Announce Type: new Abstract: Learning broad world knowledge directly from raw visual data is a fundamental capability of intelligence. We introduce UniVR, the first investigation in

Unveiling Complex Collective Behaviors from Simple Rewards

arXiv:2607.12861v1 Announce Type: cross Abstract: Multi-agent Reinforcement Learning (MARL) holds great potential for robot swarms, but the black-box nature of neural policies complicates strategic an

agentsarxiv-cs-ai

UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies

arXiv:2607.12892v1 Announce Type: cross Abstract: Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect

local-aiarxiv-cs-ai