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arXiv:2606.27883v1 Announce Type: new Abstract: In stealth-constrained swarm robotics, visual communication provides a critical alternative to active radio transmissions, which might be jammed. This r

agentsarxiv-cs-ro

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Symmetry-Aware Transformer Training for Automated Planning

DGX agent

arXiv:2508.07743v2 Announce Type: replace Abstract: While transformers excel in many settings, their application in the field of automated planning is limited. Prior work like PlanGPT, a state-of-the-

safetyarxiv-cs-ai

29 Jun 2026

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation

arXiv:2508.06115v3 Announce Type: replace Abstract: Semantic segmentation in open-vocabulary scenarios presents significant challenges due to the wide range and granularity of semantic categories. Exi

TA-SparseMG: Trend-Aware Sparse Forecasting via Multi-Scale Gating for Long-Term Time Series

model-releasesarxiv-cs-lg

arXiv:2606.27908v1 Announce Type: new Abstract: Long-term time series forecasting finds extensive applications in domains such as power demand, traffic flow, meteorological observation, and renewable

Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction

arXiv:2510.03117v2 Announce Type: replace Abstract: This study focuses on a challenging yet promising task, Text-to-Sounding-Video (T2SV) generation, which aims to generate a video with synchronized a

Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits

arXiv:2602.09456v2 Announce Type: replace Abstract: We propose an algorithmic framework, Offline Estimation to Decisions (OE2D), that efficiently reduces contextual bandit learning with general reward

Tandem Reinforcement Learning with Verifiable Rewards

arXiv:2606.28166v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capability of large language models, reaching expert or e

TempAct: Advancing Temporal Plausibility in Autoregressive Video Generation via Planner-Executor RL

arXiv:2606.28016v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models enable low-latency streaming generation by synthesizing videos chunk by chunk with cached visual context, but

Temporal Convolutional Autoencoder for Interference Mitigation in FMCW Radar Altimeters

arXiv:2505.22783v2 Announce Type: replace-cross Abstract: Reliable altitude estimation with frequency-modulated continuous wave (FMCW) radar altimeters is increasingly a challenge due to in-band inter

Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection

arXiv:2606.27655v1 Announce Type: new Abstract: Accurately localizing and segmenting small targets in low signal-to-noise ratio (SNR) infrared sequences remains a challenging task. Since targets are o

local-aiarxiv-cs-cv

TeRoR: Decoupled Temporal Rotation with Relational Circular Region for Temporal Knowledge Graph Embedding

arXiv:2606.27651v1 Announce Type: new Abstract: In recent years, with the emergence of Temporal Knowledge Graphs (TKGs), research on learning entity and relation representations in TKGs has attracted

Tessellating The Earth

arXiv:2606.27514v1 Announce Type: new Abstract: Geolocation encoders, which map geographic coordinates to learned representations, are emerging as an effective means of capturing visual and non-visual

local-aiarxiv-cs-cv

Hardware

Test-Input Generation for Tensor Programs: What Actually Finds Kernel Bugs

arXiv:2606.27396v1 Announce Type: cross Abstract: Test-input generation for tensor kernels is folkloric. Most projects pick a representative shape and dtype, run a fixed-shape allclose-style check, an

hardwarearxiv-cs-lg

Text as Illumination: Spatial Contrastive Retinex Learning for Language-guided Medical Image Segmentation

arXiv:2606.27794v1 Announce Type: new Abstract: Language-guided Medical Image Segmentation (LMIS) has shown great potential to improve the delineation of anatomical structures and lesions by integrati

TextDS: Parameter-Efficient Representation Alignment for Scene Text Detection under Distribution Shifts

arXiv:2606.28077v1 Announce Type: new Abstract: In real-world deployments, scene text detectors inevitably face distribution shifts beyond the training distribution. Prior work often depends on large-

Tutorials

Textual Belief States for World Models: Identifiable Representation Learning Under Strict Mediation

arXiv:2606.27681v1 Announce Type: cross Abstract: World models in partially observed environments rely on latent representations that summarize interaction history, but in many modern LLM-based archit

tutorialsarxiv-cs-cl

Hardware

The Context-Ready Transformer

arXiv:2606.27538v1 Announce Type: cross Abstract: We introduce the context-ready transformer, a new recurrent neural network architecture built from a D-layer transformer block that pre-contextualizes

hardwarearxiv-cs-ai

The Curse of Multiple Mediators: Hidden Interaction Effects in Activation Patching

arXiv:2606.27510v1 Announce Type: cross Abstract: Activation patching is the primary tool in mechanistic interpretability. It attributes causal responsibility for a model behavior to each of its indiv

researcharxiv-cs-cl

The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails

arXiv:2606.27462v1 Announce Type: cross Abstract: The global minimum-variance portfolio (GMVP) is the canonical decision built from an estimated covariance matrix, yet covariance estimators are univer

Applications

The Minimal Search Space for Conditional Causal Bandits

arXiv:2502.06577v3 Announce Type: replace-cross Abstract: Causal knowledge can be used to support decision-making problems. This has been recognized in the causal bandits literature, where a causal (m

applicationsarxiv-cs-ai

The Remittance Blueprint: Data-driven Intelligence for Sri Lanka

arXiv:2606.28190v1 Announce Type: cross Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data an

The Shift Toward Open and Reproducible AI Research

arXiv:2606.16974v3 Announce Type: replace Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices. Several studies have identified methodol

The Signal-Coverage Matrix: Stratifying Type and Semantic Errors in Statement Autoformalization

model-releasesarxiv-cs-cl

arXiv:2606.28013v1 Announce Type: new Abstract: Headline type-correctness (TC%) of LLM autoformalization has climbed from sim53% to sim76% in two years, yet this scalar conceals which errors each meth

The Simulacrum: Decision-Theoretic Pretraining for Near-Optimal Time-Series Forecasting and Inference

arXiv:2606.27711v1 Announce Type: cross Abstract: We introduce a neural network-based framework for learning time series estimators through a process we term decision-theoretic pretraining. Analysts s

The Weakest Link Tells It All: Outcome-Supervised Process Reward Modeling via Learnable Credit Assignment

arXiv:2606.27739v1 Announce Type: new Abstract: Process reward models (PRMs) enhance the reasoning capabilities of large language models (LLMs) by providing fine-grained feedback, yet training PRMs ty

There and Back Again: A Flexible-Frame Transformer for Multi-Exposure Fusion

arXiv:2606.27905v1 Announce Type: new Abstract: Multi-exposure fusion (MEF) brings the dynamic range of conventional cameras closer to that of human vision, producing images with rich scene content. G

ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation

arXiv:2606.27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Opti

ToolPrivacyBench: Benchmarking Purpose-Bound Privacy in Tool-Using LLM Agents

arXiv:2606.28061v1 Announce Type: cross Abstract: Large language models (LLMs) have increasingly moved from standalone text generation systems to agents that invoke external tools, access environments

Toward Robust In-Context Segmentation via Concept Guidance

arXiv:2606.28149v1 Announce Type: cross Abstract: In-context segmentation (ICS) requires a model to segment target regions in a query image using only a few reference images and their corresponding ma

Towards Automating Scientific Review with Google's Paper Assistant Tool

arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem pr

Towards Benign Memory Forgetting for Selective Multimodal Large Language Model Unlearning

arXiv:2511.20196v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can inadvertently memorize privacy-sensitive information during training. While existing unlearning methods

Applications

Towards Evaluation of Implicit Software World Models in Coding LLMs

arXiv:2606.27406v1 Announce Type: cross Abstract: Software engineering, whether performed by humans or by AI agents, requires reasoning about how software behaves. We call the internal model that supp

applicationsarxiv-cs-ai

Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework

arXiv:2606.27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns rega

Tutorials

Towards Reliable Recommender Systems for Rating Data

arXiv:2412.20802v3 Announce Type: replace-cross Abstract: Recommender systems are widely used in the digital landscape to match users with content fitting their preferences. However, growing concerns

tutorialsarxiv-cs-lg

Towards Value-Constrained Credit Assignment in Fully Delegated AI Cooperatives

arXiv:2606.28217v1 Announce Type: cross Abstract: We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and partic

ToxiREX: A Dataset on Toxic REasoning in ConteXt

arXiv:2606.27981v1 Announce Type: new Abstract: We introduce a new, contextual, multilingual dataset called ToxiREX: Toxic REasoning in ConteXt. The dataset consists of threads of Reddit comments and

researcharxiv-cs-cl

Training-free Truthfulness Detection via Sparse MLP Value Vectors

model-releasesarxiv-cs-cl

arXiv:2509.17932v2 Announce Type: replace Abstract: Large language models (LLMs) are prone to generating factually incorrect content, motivating methods for assessing truthfulness from internal model

Training-free Uncertainty Guidance for Complex Visual Tasks with MLLMs

arXiv:2510.00705v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) often struggle with fine-grained perception, such as identifying small objects in high-resolution images or

researcharxiv-cs-cv

Training Observable Control Policies to Expose Agent State Through Actions

arXiv:2606.27609v1 Announce Type: new Abstract: Physical or operational constraints often impose communications limitations on autonomous agents. Such limitations complicate monitoring or multiagent c

safetyarxiv-cs-lg

Tutorials

Translation as a Bridging Action: Transferring Manipulation Skills from Humans to Robots

arXiv:2606.28133v1 Announce Type: cross Abstract: We study whether we can learn novel manipulation skills from human actions to a bi-manual robot with parallel grippers. Human action data is cheap, ab

tutorialsarxiv-cs-cv

TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

model-releasesarxiv-cs-lg

arXiv:2506.10355v2 Announce Type: replace Abstract: Many real-world applications collect data in a streaming environment, where learning tasks are encountered sequentially. This necessitates continual

Triadic Werewolf: A Jester Role for Multi-Hop Theory of Mind in LLMs

arXiv:2606.27909v1 Announce Type: cross Abstract: Theory-of-mind evaluations of large language models typically use dyadic social-deduction games, where every observable cue points to a single hidden

TruEye: Fine-Grained Detection of AI-Generated Human Subjects in Images

arXiv:2606.27505v1 Announce Type: new Abstract: AI generated images are proliferating across the Internet. While some are used for entertainment, others are weaponized for fraud and social engineering

local-aiarxiv-cs-cv

TRUST: Efficient Abdominal Trauma Recognition via Image-to-Ultrasound-Video Transfer Learning

arXiv:2606.27777v1 Announce Type: new Abstract: Abdominal ultrasound is indispensable for rapid, noninvasive trauma triage. However, interpreting the subtle dynamic cues embedded in continuous scannin

Trust Region Masking for Long-Horizon LLM Reinforcement Learning

arXiv:2512.23075v5 Announce Type: replace-cross Abstract: Policy gradient methods for Large Language Models optimize a policy pi_heta via a surrogate objective computed from samples of a rollout polic

Trustworthy Predictive Distributions for Tail Events with Semiparametric Diagnostic Transport Maps

arXiv:2603.11229v2 Announce Type: replace-cross Abstract: Machine learning forecast systems are moving beyond point predictions to full predictive distributions for future outcomes y conditional on co

local-aiarxiv-cs-lg

Two-Stage Cross-Domain Cervical Abnormality Screening with Cytopathological Image Synthesis and Knowledge Distillation

arXiv:2606.27678v1 Announce Type: new Abstract: Cross-domain diagnosis remains a major challenge in cervical cell pathology due to pronounced domain shifts across institutions and the subtle visual di

Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition

arXiv:2606.27939v1 Announce Type: cross Abstract: Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remain