Search: “models”

StarDojo: Benchmarking Open-Ended Behaviors of Agentic Multimodal LLMs in Production-Living Simulations with Stardew Valley

arXiv:2507.07445v3 Announce Type: replace Abstract: Autonomous agents navigating human society must master both production activities and social interactions, yet existing benchmarks rarely evaluate t

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Model Releases

TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents

DGX agent

arXiv:2606.28480v1 Announce Type: cross Abstract: As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader ra

model-releasesarxiv-cs-ai

30 Jun 2026

Variance Reduction on the Camera Axis: Multi-View Score Distillation for 3D

arXiv:2606.29964v1 Announce Type: new Abstract: Score distillation turns a pretrained 2D diffusion model into a 3D generator, but the per-step gradient is estimated from a single randomly chosen view:

When Does Overlap Help? OSU-Mem and a Cell-Conditional Analysis of Trajectory Memory for LLM Agents

arXiv:2606.28376v1 Announce Type: cross Abstract: Long-horizon large language model (LLM) agents accumulate interaction trajectories that quickly exceed any practical prompt budget, and existing memor

When Prices Double in a Week: Forecasting of Agricultural Volatility in Import-Isolated Markets

arXiv:2606.29248v1 Announce Type: new Abstract: Vegetable prices in Sri Lanka are highly volatile because the market is largely import-isolated, so supply disruptions quickly drive prices up. This stu

researcharxiv-cs-lg

Safety

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

arXiv:2606.30587v1 Announce Type: cross Abstract: Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs a

safetyarxiv-cs-ai

XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation

arXiv:2412.15529v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLM

A Multi-Attribute Latent Space for Visual Analysis of Watches

arXiv:2606.27897v1 Announce Type: new Abstract: We present a design rationale, embedding model, and interactive visual-analysis system for exploring large wristwatch collections through heterogeneous

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

model-releasesarxiv-cs-cl

arXiv:2606.28044v1 Announce Type: new Abstract: In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditiona

Building a Scalable, Reproducible, Evaluatable, and Closed-Loop Simulation Environment Foundation for Embodied Intelligence Cloud-Native Simulation Infrastructure for Embodied Intelligence Training, Evaluation, and Data Collection

model-releasesarxiv-cs-ro

arXiv:2606.27962v1 Announce Type: new Abstract: This paper presents a cloud-native simulation infrastructure framework for embodied intelligence that supports large-scale training, standardized evalua

Safety

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training

arXiv:2602.16065v2 Announce Type: replace-cross Abstract: As artificial intelligence (AI)-generated content proliferates, models are increasingly trained on their own outputs, risking progressive degr

safetyarxiv-cs-ai

Tutorials

CBD: API-Only LLM Black-Box Unlearning through Controlled Behavioral Divergence

arXiv:2606.27683v1 Announce Type: cross Abstract: Edge devices increasingly invoke large language models (LLMs) through API services for context aware edge intelligence, while edge generated data may

tutorialsarxiv-cs-ai

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

arXiv:2504.16116v4 Announce Type: replace-cross Abstract: The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software v

FoggyTrust: Robust Federated Learning with Hierarchical Trust Networks

arXiv:2606.27622v1 Announce Type: new Abstract: Byzantine-robust federated learning seeks to protect distributed model training from malicious or corrupted clients without requiring access to their pr

Freshness and the Limits of Heuristic Trend Detection in Temporal RAG

arXiv:2509.19376v2 Announce Type: replace-cross Abstract: We present a lightweight, model-agnostic temporal layer for RAG and use cybersecurity data to separate two problems that are usually conflated

Tutorials

HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech

arXiv:2606.28249v1 Announce Type: cross Abstract: Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised Fine-Tun

tutorialsarxiv-cs-cl

Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shading

arXiv:2606.28144v1 Announce Type: new Abstract: Reconstructing high-fidelity, relightable 3D avatars from a single in-the-wild image is a challenging ill-posed problem, primarily hindered by the scarc

Parameter-Efficient Continuous-Variable Photonic Quantum Neural Networks for Edge Quantum AI: Demonstration in Oral Cancer Detection

arXiv:2606.28252v1 Announce Type: cross Abstract: Early detection of oral cancer markedly improves clinical outcomes, yet specialized diagnostic tools remain scarce in low-resource settings. Smartphon

Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting

arXiv:2606.27821v1 Announce Type: cross Abstract: Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting re

Safety

PhysisForcing: Physics Reinforced World Simulator for Robotic Manipulation

arXiv:2606.28128v1 Announce Type: cross Abstract: Video generation models have emerged as a promising paradigm for embodied world simulation. However, both general-domain video generators and robot-sp

safetyarxiv-cs-ai

Prism Transformer: Progressive Head Schedules for Hierarchical Attention Processing

arXiv:2606.27449v1 Announce Type: new Abstract: Multi-head attention conventionally partitions the hidden dimension equally across all heads at every layer, enforcing an identical representational sub

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

arXiv:2509.03704v2 Announce Type: replace Abstract: Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating

RANSAC Scoring Done Right

arXiv:2606.27385v1 Announce Type: cross Abstract: The most widely used RANSAC variants score candidate models by counting inliers or summing per-point scores that saturate beyond a residual threshold.

Applications

RelBall: Relation Ball with Quaternion Rotation for Knowledge Graph Completion

arXiv:2606.27967v1 Announce Type: new Abstract: Real-world knowledge graphs are often incomplete, lacking many valid facts. Knowledge Graph Completion (KGC) aims to predict missing links using known t

applicationsarxiv-cs-ai

RS-Diffuser: Risk-Sensitive Diffusion Planning with Distributional Value Guidance

arXiv:2606.27766v1 Announce Type: cross Abstract: Offline reinforcement learning enables policy learning from fixed datasets without additional environment interaction, making it appealing for safety-

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

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

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

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

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

When One Adapter Speaks for Many: Discovering Low-Rank Redundancy in Continual Fine-Tuning

arXiv:2606.28117v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become the standard tool for parameter-efficient fine-tuning of large pretrained models. When applied sequentially across

Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents

arXiv:2606.26627v1 Announce Type: cross Abstract: Large language model agents increasingly query databases, search document collections, call external APIs, remember past interactions, and act on a us

auto-psych: Automating the science of mind using agent-driven theory discovery and experimentation

arXiv:2606.26460v1 Announce Type: new Abstract: AI-based scientific automation is increasingly possible by using agents to generate hypotheses, design experiments, and analyze data. Data collection is

Detecting and Controlling Sycophancy with Cascading Linear Features

arXiv:2606.26155v1 Announce Type: new Abstract: Interpreting and controlling model behaviors through activation steering methods requires many pairs of contrastive samples that clearly exhibit desired

researcharxiv-cs-ai

Disco-LoRA: Disentangled Composition of Content, Style, and Motion for Multi-concept Video Customization

arXiv:2606.26668v1 Announce Type: cross Abstract: Video customization based on Text-to-Video (T2V) models aims to learn specific features from reference data to generate controllable videos. While sig

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

arXiv:2606.26120v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirect

researcharxiv-cs-cl

Error-Conditioned Neural Solvers

arXiv:2606.27354v1 Announce Type: cross Abstract: Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical tas

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning

model-releasesarxiv-cs-cl

arXiv:2606.26629v1 Announce Type: cross Abstract: Weight-space regularization methods such as Elastic Weight Consolidation (EWC) are the standard approach to catastrophic forgetting in continual learn

Information-Aware KV Cache Compression for Long Reasoning

arXiv:2606.26875v1 Announce Type: cross Abstract: Reasoning capability has advanced rapidly in large language models (LLMs), leading to an increasing size of key-value (KV) cache in both prefilling an

Inherited Circuits, Learned Semantics: How Fine-Tuning Creates Evasion Vulnerabilities Invisible to Standard Evaluation

arXiv:2606.27091v1 Announce Type: cross Abstract: LLMs fine-tuned for security classification are usually evaluated on held-out examples from the same distribution as their training data. We show that

Learning from Equivalence Queries, Revisited

arXiv:2604.04535v2 Announce Type: replace Abstract: Modern machine learning systems, such as generative models and recommendation systems, often evolve through a cycle of deployment, user interaction,

researcharxiv-cs-lg

Learning to Select Maximum Clique Algorithms: From Traditional Machine Learning to a Dual-Channel Hybrid Neural Architecture

arXiv:2508.08005v4 Announce Type: replace-cross Abstract: The Maximum Clique Problem (MCP) is an NP-hard problem with wide-ranging applications in fields such as bioinformatics, network science, and s

Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds

arXiv:2606.26964v1 Announce Type: new Abstract: As embodied AI and world models increasingly operate in dynamic 3D environments, visual perception must move beyond passively interpreting given observa

Mask to Concept: Auto-Promptable SAM3 via Efficient Test-Time Concept Embedding Search for Few-Shot Annotation

arXiv:2606.26711v1 Announce Type: new Abstract: Transforming foundation segmentation models from human-prompted tools into auto-promptable annotators is critical for scalable medical data annotation.

MKG-RAG-Bench: Benchmarking Retrieval in Multimodal Knowledge Graph-Augmented Generation

arXiv:2606.26458v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over knowledge graphs has emerged as a promising approach for grounding large language models, yet existing benchma

OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents

arXiv:2606.26350v1 Announce Type: new Abstract: Although large language model agents are increasingly applied to quantitative-finance workflows, their evaluation remains fragmented across isolated tas

Parametric Open Source Games

arXiv:2606.27068v1 Announce Type: cross Abstract: Open-source game theory studies agents whose behavior may depend on one another's decision procedures, but most existing models use discrete or symbol

PersistentKV: Page-Aware Decode Scheduling for Long-Context LLM Serving on Commodity GPUs

arXiv:2606.26666v1 Announce Type: new Abstract: Autoregressive large language model (LLM) serving is increasingly limited by key-value (KV) cache movement rather than dense matrix multiplication. Mode

Applications

PhysiFormer: Learning to Simulate Mechanics in World Space

arXiv:2606.27364v1 Announce Type: new Abstract: We present PhysiFormer, a diffusion transformer for physically-plausible 3D object motion. Unlike video world models that operate in view-dependent pixe

applicationsarxiv-cs-cv

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP

arXiv:2606.26794v1 Announce Type: cross Abstract: CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text ali