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arXiv:2607.09600v2 Announce Type: replace Abstract: Enhancing the reasoning capabilities of large language model (LLM) agents requires effective orchestration of diverse expert models and tools. Howev

agentsarxiv-cs-ai

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AlgoWorlds: Benchmarking Tool Use for Global Optimization in Algorithmic Worlds

DGX agent

arXiv:2608.29397v1 Announce Type: new Abstract: Tool-use benchmarks generally evaluate whether an agent completes a workflow using appropriate tools and valid arguments. However, feasibility alone is

model-releasesarxiv-cs-cl

1 Sept 2026

AQ3D: Adaptive Query Transformer for 3D Instance Segmentation

arXiv:2608.30618v1 Announce Type: new Abstract: Transformer-based decoders for 3D instance segmentation typically commit to a fixed number of queries and positional modeling calibrated on the training

researcharxiv-cs-cv

Bayesian-Optimized Superpixel-GrabCut for Traceable Optic Disc Segmentation

arXiv:2608.29196v1 Announce Type: new Abstract: Optic disc (OD) segmentation is essential for diagnosing ophthalmic pathologies from retinal fundus images. However, prevailing deep learning approaches

Beyond Polarization: The Generative Constraint of Chain-of-Thought in Pointwise Reranking

arXiv:2608.30398v1 Announce Type: new Abstract: In pointwise document reranking, Chain-of-Thought models typically underperform direct scoring models. While existing diagnostics attribute this to infe

safetyarxiv-cs-cl

Correctness Forensics for Batch Speculative Decoding: Diagnosing the Ragged Tensor Problem

arXiv:2510.22876v4 Announce Type: replace-cross Abstract: Inference optimizations are routinely evaluated by throughput alone, without verifying output correctness. We conduct a forensic analysis of b

Deploying DeepSeek 175B Locally on a Single Consumer-Grade RTX 4060 Laptop with 32GB RAM for 200k-Scale Protein-Ligand Virtual Screening

arXiv:2608.30877v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated exceptional performance in protein-ligand interaction prediction, but state-of-the-art

DreamX-Creator: Democratizing Native Audio-Video Generation at 2K Resolution

arXiv:2608.31106v1 Announce Type: new Abstract: Recent video generators often omit audio or synthesize it in a separate stage, limiting reciprocal modeling of visual dynamics and acoustic events. We p

researcharxiv-cs-cv

Enhancing Low-Resource Language Reasoning via High-Resource Language Feature Transfer

arXiv:2608.30462v1 Announce Type: cross Abstract: Large language models exhibit substantial performance variation across languages, even when solving semantically equivalent tasks. Existing analyses o

Equivariant Sheaf Neural Networks: Learning Geometric Transport on Graphs

arXiv:2608.28853v1 Announce Type: cross Abstract: Equivariant graph neural networks provide a principled way to model geometric systems, but efficient first-order architectures remain limited in how v

researcharxiv-cs-ai

EviAnchor: Mitigating Hallucinations in Large Vision-Language Models via Regional Visual Evidence Compensation

arXiv:2608.29092v1 Announce Type: new Abstract: Large vision-language models (LVLMs) frequently generate content unsupported by visual inputs. Preliminary experiments show that visual evidence is prim

researcharxiv-cs-ai

Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment

arXiv:2608.29978v1 Announce Type: new Abstract: Large language models are increasingly required to generate responses that satisfy multiple competing objectives. Since optimal trade-offs depend on bot

safetyarxiv-cs-cl

FractureFields: Contact-Aware Binary Multi-Field Transfer for Fractured 3D Gaussian Simulation

arXiv:2608.28982v1 Announce Type: new Abstract: Physics-integrated 3D Gaussian representations make it possible to simulate image-reconstructed assets directly as particles, but current Gaussia-MPM pi

Agents

From Extraction to Governed Memory: Multi-Agent Knowledge Graph Construction with Domain-Expert Review

arXiv:2608.28642v1 Announce Type: new Abstract: Knowledge graphs used by agentic systems are often treated as flat stores of extracted triples, with little record of who owns a fact, why it was admitt

agentsarxiv-cs-ai

From Question-First to Analyst-First: Domain-Expert Skills and Verified Knowledge Compilation for Proactive Enterprise Analytics

arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente

HiRS-Agent: A Hierarchical Multi-Agent System for Reliable Long-Horizon Remote Sensing Task Solving

arXiv:2608.30672v1 Announce Type: new Abstract: Recent advances in large language models and multimodal models have pushed remote sensing (RS) processing from simple perception models to agentic syste

Agents

HybridWorldSim: A Scalable and Controllable High-fidelity Simulator for Autonomous Driving

arXiv:2511.22187v4 Announce Type: replace Abstract: Realistic and controllable simulation is critical for advancing end-to-end autonomous driving, yet existing approaches often struggle to support nov

agentsarxiv-cs-cv

Influence Is Not Authority: When Causal Guardrail Signals Make Legitimate Tool Use Look Like an Attack in Tool-Using LLM Agents

arXiv:2608.29942v1 Announce Type: cross Abstract: The key limitation of current state-of-the-art influence-based guardrails is that they do not reliably distinguish a legitimate, user-authorized actio

LoGo: Token-Level Dynamic Local-Global Attention

arXiv:2608.29539v1 Announce Type: new Abstract: As context lengths scale, attention increasingly becomes a primary computational bottleneck in large language models. Standard Transformers remain power

LongGuard: Mechanistic Analysis and Training-Free Mitigation of Long-Context Failure in Safety Guardrails

arXiv:2608.27580v2 Announce Type: replace Abstract: Safety guardrails serve as the last line of defense against harmful inputs and outputs of large language models (LLMs), yet they are trained and eva

Manaca-1B: An Open, Reproducible Brazilian-Portuguese Language Model and a Tokenizer-Aware, Paired Evaluation

arXiv:2608.30114v1 Announce Type: new Abstract: Brazilian Portuguese remains under-served by open language models, and the few that exist are difficult to reproduce and are often compared without meas

MedCache: Efficient and Temporally Valid Memory for Longitudinal Clinical Agents

arXiv:2608.29528v1 Announce Type: new Abstract: Longitudinal clinical agents must maintain an evolving patient state from evidence distributed across visits, time points, and specialties. However, how

MedTVL: Harnessing Vision and Language for Medical Time Series Classification

arXiv:2608.28605v1 Announce Type: new Abstract: Recent advancements in multimodal learning for medical time series (MedTS) classification highlight the benefits of integrating complementary modalities

researcharxiv-cs-ai

MUDDLE: Measuring Understanding of Documents under Distractor and Length Effects

arXiv:2608.29477v1 Announce Type: cross Abstract: Document question-answering systems increasingly answer questions over collections of retrieved documents rather than one clean source, so robustness

Multimodal Shared Latent Representation of Narration, Microscope and iOCT Images for Phase Recognition in Vitreoretinal Surgery

arXiv:2608.31065v1 Announce Type: new Abstract: Surgical phase recognition is key to context-aware computer-assisted feedback in vitreoretinal procedures, yet the scarcity of synchronized multimodal i

safetyarxiv-cs-cv

One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning

arXiv:2608.31096v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires a model to incrementally learn tasks that contain new classes without accessing earlier training data while pr

Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

arXiv:2608.30317v1 Announce Type: cross Abstract: Online dynamic origin-destination (OD) matrix estimation (DODE) calibrates time-dependent OD demand to reproduce observed link-flow trajectories. In o

PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies

arXiv:2608.30378v1 Announce Type: cross Abstract: Direct vision-language-action policies generate continuous robot actions efficiently, but standard behavior cloning leaves two complementary gaps: the

Local Ai

PhysVR: Vision-Language Model Guided Interference-aware Temporal Feature Refinement for Remote Physiological Measurement

arXiv:2608.29663v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables contactless physiological measurement from facial videos, yet its subtle pulse-related variations are easily

local-aiarxiv-cs-cv

Hardware

PowerSlider: Exploiting Phase Asymmetry for LLM Serving under Demand Response

arXiv:2608.21719v1 Announce Type: cross Abstract: AI inference clusters are increasingly constrained by instantaneous power, not just energy: grid operators condition new capacity on demand response,

hardwarearxiv-cs-ai

Tutorials

Pretrained, Curriculum-Tuned, and Ensembled: A Tracer-Aware Interactive Segmentation Pipeline for AutoPET V

arXiv:2608.30844v1 Announce Type: cross Abstract: Interactive lesion segmentation in whole-body PET/CT requires a model to provide a strong initial prediction while also responding efficiently to spar

tutorialsarxiv-cs-ai

PRIME: Mitigating Subgroup Optimization Competition in Shared CTR Top Networks with Plug-in Residual Input-Conditioned Mixture of Expert

arXiv:2608.30449v1 Announce Type: new Abstract: Click-through rate (CTR) models vary in feature-interaction design, yet their top networks usually remain a single multilayer perceptron shared by all e

researcharxiv-cs-lg

Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

arXiv:2608.30344v1 Announce Type: new Abstract: Most shape reconstruction methods assume measurements defined over planar sensing domains, such as RGB images or depth maps. In this paper, we use a cur

researcharxiv-cs-cv

Quantifying and Mitigating Korean Jamo-Level Typographical Vulnerabilities in Large Language Models

arXiv:2608.30229v1 Announce Type: new Abstract: Korean introduces an additional typographical perturbation level not captured by ordinary character-level edit models: because syllable blocks are inter

Revolutionizing Turn-by-Turn Navigation with Cloud-Edge Deep Learning

arXiv:2608.29073v1 Announce Type: new Abstract: Turn-by-turn (TBT) navigation systems are integral to modern driving experiences, providing real-time audio instructions to guide drivers safely to dest

Selection, Representation, and Execution in Sparse Fourier Neural Operators

arXiv:2608.30070v1 Announce Type: new Abstract: Sparse representations are often expected to make models smaller and also reduce inference cost. For Fourier Neural Operators (FNOs), these objectives a

Self-Aware Active Learning Enables Continual Improvement in Autonomous Driving

arXiv:2608.29772v1 Announce Type: new Abstract: Learning-based autonomous driving (AD) systems can perform reliably in familiar conditions, yet rare distribution shifts and long-tail events remain a m

safetyarxiv-cs-ro

Sequential Trajectories and Simultaneous Blending: Multi-Emotion Modeling for Instruction-Following TTS

arXiv:2608.30325v1 Announce Type: new Abstract: Natural-language instructions enable flexible control of synthesized speech, yet emotional TTS systems primarily model a single utterance-level affect,

safetyarxiv-cs-cl

Applications

SGE: Semantically-Guided Exploration for Unstructured Environments via Image-Space Waypoint Sampling

arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic s

applicationsarxiv-cs-ai

SkillForge: Compositional Skill Synthesis with Verification-in-the-Loop for Generating Formally Verified Dafny Programs

arXiv:2608.29841v1 Announce Type: new Abstract: Generating formally verified programs from natural language remains challenging: existing approaches either produce code in a single pass without recour

Applications

SMILE: Smooth Motion for Improved Long-Horizon VLA Execution

arXiv:2608.29432v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models reduce inference cost by executing multiple actions per call, but longer horizons often degrade accuracy because raw

applicationsarxiv-cs-ro

Sparse Competition during Training For the Emergence of Specialized Modules

arXiv:2608.30978v1 Announce Type: new Abstract: Modularity in deep neural networks has been proposed as a means of improving both interpretability and training by promoting disentangled representation

researcharxiv-cs-lg

Structure Aware Neural Architecture Search for Mixture of Experts

arXiv:2608.29817v1 Announce Type: new Abstract: Neural Architecture Search (NAS) has so far rarely been applied to Mixture-of-Experts (MoE) models, and existing MoE designs leave the alignment between

To Copy or Not to Copy: Copying Is Easier to Induce Than Recall

arXiv:2601.12075v2 Announce Type: replace Abstract: Language models used in retrieval-augmented settings must arbitrate between parametric knowledge stored in their weights and contextual information

researcharxiv-cs-cl

TopoAgent: A Structure-Aware Perception-to-Reasoning Framework for Diagram-to-Graph Topology Extraction with Large Vision-Language Models

arXiv:2608.28701v1 Announce Type: new Abstract: Diagram-to-graph topology extraction aims to extract a graph of entities and their connections from a structural diagram. This task remains challenging

Towards a Systems Foundation for Agentic Skills: Architecture, Lifecycle, and Security

arXiv:2608.29596v1 Announce Type: new Abstract: Autonomous large language model (LLM) agents increasingly face reliability, context consumption, and execution stability bottlenecks when deployed on co

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection

arXiv:2508.20766v2 Announce Type: replace-cross Abstract: Safety alignment in Large Language Models (LLMs) often involves mediating internal representations to refuse harmful requests. Recent research

VoiceCodeBench: Evaluating Exact Structured-Token Recovery in Automatic Speech Recognition

arXiv:2608.28916v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems are commonly evaluated with word error rate (WER), yet many voice workflows depend on exact written values fo