Search: “routing”

What Should a Large Language Model See? Physical Invariants as a Data Representation for PDE Discovery

arXiv:2608.25189v1 Announce Type: new Abstract: Understanding how molecular interactions govern macroscopic behaviour is a central challenge in molecular sciences. However, conventional theory buildin

27 Aug 2026

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Evaluating Language Models on Cross-Language Code Functional Equivalence

DGX agent

arXiv:2608.23961v1 Announce Type: cross Abstract: Background: Large Language Models (LLMs) have demonstrated strong performance across a variety of code-understanding tasks, leading many to believe th

model-releasesarxiv-cs-ai

26 Aug 2026

Joint Optimization of Tool Creation and Use for Large Language Model Agents

arXiv:2608.24571v1 Announce Type: new Abstract: Tool-augmented language models are bounded by the APIs humans bothered to write; existing tool-creation systems patch this by prompting a frozen LLM at

safetyarxiv-cs-ai

Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents

arXiv:2608.24087v1 Announce Type: cross Abstract: Current LLM agent systems decide delegation before reasoning begins (a router picks a model) or after a response is complete (a verifier scores it and

safetyarxiv-cs-ai

On-policy Distillation with Verifiable Reward

arXiv:2608.24696v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) and on-policy distillation (OPD) have become two widely adopted paradigms for post-training larg

safetyarxiv-cs-ai

PinSieve: Production Selective VLM Serving and a Governed Memory Flywheel for Enterprise Content-Quality Triage

arXiv:2608.24040v1 Announce Type: new Abstract: Enterprise AI agents in production often need to be bounded, stateful, observable, and governable rather than fully autonomous. We present PinSieve, a p

agentsarxiv-cs-lg

Restoring Without Forgetting: Continual Learning Across Image Degradations

arXiv:2608.23799v1 Announce Type: cross Abstract: Recent progress in image restoration has converged on all-in-one architectures that jointly handle multiple degradations within a single network. Thes

RetrievalFormer: A Dual-Encoder Transformer for Efficient Approximate Nearest Neighbor Retrieval and Cold-Item Recommendation

arXiv:2608.24079v1 Announce Type: cross Abstract: A shared search-and-recommendation index must score new items from features alone because search has no exploration slot. In a public log covering bot

researcharxiv-cs-lg

ROI-Gated SAHI: Content-Adaptive Slicing-Based Inference for Efficient Object Detection

arXiv:2608.23923v1 Announce Type: new Abstract: Slicing-Aided Hyper Inference (SAHI) improves small object detection in high-resolution images but often spends substantial compute on background tiles.

safetyarxiv-cs-cv

Unlocking the power of partnership: How humans and machines can work together to improve face recognition

arXiv:2510.02570v2 Announce Type: replace Abstract: Human review of consequential decisions by face recognition algorithms creates a collaborative human-machine system. We establish the circumstances

Velocity-coupled Representation Refinement for Satellite Orbit Prediction

arXiv:2608.23728v1 Announce Type: new Abstract: Satellite orbit prediction, which aims to forecast future orbital trajectories from historical observations, is important for collision warning and safe

ClawProBench: Trace-Aware Evaluation of AI Agents with Runtime Coverage and Frozen Workplace-Style Holdouts

arXiv:2608.22510v1 Announce Type: new Abstract: Agent benchmarks often evaluate only final answers even when agents run on stateful runtimes. We argue this under-specifies what is being evaluated: the

Applications

MEMONDEMAND: A Memory Management System for Large-Scale Enterprise Data

arXiv:2608.22141v1 Announce Type: new Abstract: Enterprise repositories are large, heteroge- neous, and continuously updated, making re- trieval difficult when efficient access, source- faithful evide

applicationsarxiv-cs-ai

More Experts, Worse Dynamics: Inverse Scaling and Spectral Bias in Mixture-of-Experts State-Space Models

arXiv:2608.21840v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures are commonly motivated as a way to increase expressivity by decomposing complex systems into simpler local dynami

safetyarxiv-cs-lg

SA-RSQ: A Versatile Sparse Representation Framework for Multi-modal Recommender Systems

arXiv:2608.22979v1 Announce Type: new Abstract: Deploying high-dimensional multimodal features in industrial recommender systems incurs substantial storage and latency overhead. Hard quantization is c

Semantic Compression Trees: Multi-Resolution Knowledge Retrieval via Hierarchical Semantic Residuals

arXiv:2608.21610v1 Announce Type: new Abstract: Retrieval-augmented generation relies mostly on flat, fixed-granularity indexes: documents are cut into uniform chunks and retrieved by similarity, disc

TSWAP: A Multilingual Retrieval-Augmented Thai Wellness Advisor

model-releasesarxiv-cs-cl

arXiv:2608.22917v1 Announce Type: new Abstract: We present TSWAP, a deployed eight-language conversational wellness advisor grounded, via retrieval-augmented generation, in a verified knowledge base o

Belief Without Behavior: Measuring the Translation of Theory of Mind into Coordinated Social Action in Vision-Language Models

arXiv:2608.20975v1 Announce Type: new Abstract: Effective social interaction requires agents to translate mental state inferences into coordinated behavioral signals across verbal and nonverbal channe

BF1: A Causal Dyadic Sparse-Attention Retrofit for Efficient Long-Context Transformers

arXiv:2608.20427v1 Announce Type: cross Abstract: Dense causal attention remains expensive at long context even when implemented with highly optimized exact kernels. We study BF1, a deterministic bloc

local-aiarxiv-cs-ai

Explainable Deepfake Detection with Feature-robust Augmentation and Evidence-grounded Explanation Optimization

arXiv:2608.20913v1 Announce Type: cross Abstract: Explainable deepfake detection extends binary classification by requiring models to not only predict authenticity but also provide interpretable justi

From Regulation to Implementation: A Critical Evaluation of LLM-Assisted Regulatory Compliance in Industry

arXiv:2608.21317v1 Announce Type: new Abstract: The European Union (EU) has emerged as a leading regulatory body in the development of sustainability and privacy regulations. While new regulation requ

GAP-SAM: A Global Artifact Prior for Generalizable AI-Generated Image Manipulation Localization

arXiv:2608.20929v1 Announce Type: new Abstract: AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel su

safetyarxiv-cs-cv

Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles

arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and

Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring

arXiv:2602.17751v2 Announce Type: replace-cross Abstract: Biodiversity loss poses a significant threat to humanity, making wildlife monitoring essential for assessing ecosystem health. Avian species a

agentsarxiv-cs-ai

Is Visual Prompting All You Need? Studying VLM Spatial Reasoning under Progressive Visual Scaffolds

arXiv:2608.21170v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced rapidly in multimodal reasoning, yet recent work shows that their failures often reflect an interaction be

Keep Your Friends Close, and the Right Neighbours Closer: Disaster-Conditioned Kernel-Regularized Graph Attention for Building Damage Classification

arXiv:2608.20548v1 Announce Type: new Abstract: Disaster damage is spatial: buildings rarely fail in isolation. Yet using spatial context for damage classification remains surprisingly underexplored,

local-aiarxiv-cs-cv

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

arXiv:2608.21100v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimod

local-aiarxiv-cs-ai

StateSight: Benchmarking Latent Spatial-State Reconstruction in Vision-Language Models

arXiv:2608.20414v1 Announce Type: new Abstract: Vision-language models are increasingly used for multimodal question answering, yet their ability to reconstruct latent spatial structure from a single

Tydra: An Efficient Hybrid Model for Tabular Data

arXiv:2608.21199v1 Announce Type: new Abstract: Transformer-based tabular foundation models such as TabPFN achieve strong predictive performance but incur quadratic computational cost with context len

researcharxiv-cs-lg

Ask Self, Ask Others: Relation Is All You Need

arXiv:2608.20172v1 Announce Type: new Abstract: Attention directly derives normalized information flow from pairwise scores. We introduce Relation, an alternative token-mixing primitive that first org

DeltaMomentum: A Key-Value based Anisotropic Momentum Update via Delta Rule

arXiv:2608.19491v1 Announce Type: cross Abstract: Most modern optimizers form their momentum as an exponential moving average (EMA) of past gradients, forgetting every direction at one fixed rate. How

researcharxiv-cs-cl

FleetSieve: Decision-Critical Profiling for SLO-Aware LLM Fleet Configuration

arXiv:2608.19659v1 Announce Type: new Abstract: Choosing tensor-parallel (TP) degrees and replica counts for an LLM serving fleet is difficult because performance is not monotonic in TP and the feasib

From Retrieved Context to Runtime Control: Adaptive Compression for Edge-based RAG

arXiv:2608.19535v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language-model responses by grounding generation in external passages, which comes with overhead: retrieve

Holtercare-Bench: A Multimodal Benchmark for Evaluating Long-Term Dynamic ECG Analysis

arXiv:2608.19297v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) excel in medical applications, most of them favor static images or short-term signals. In the critical fi

HYDRA: A Heterogeneous Chiplet DSE Framework for Serving Dynamic Hybrid LLM Workloads

arXiv:2608.19395v1 Announce Type: cross Abstract: Hybrid Transformer-Mamba large language models (LLMs) enhance long-context efficiency, but their heterogeneous computation and communication patterns

ID-VTG: Image-Disambiguated Video Temporal Grounding

arXiv:2608.20127v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) faces significant challenges when natural language queries must distinguish between multiple events involving visually si

MileGPO: Milestone Inference with Local Evidence for Graph-Based Policy Optimization of Long-Horizon LLM Agents

arXiv:2608.19803v1 Announce Type: cross Abstract: Credit assignment is challenging in long-horizon agentic reinforcement learning, where supervision often comes only from final rewards. Existing metho

local-aiarxiv-cs-ai

Object-aware graph matching network for cross-domain remote sensing image localization

arXiv:2511.02489v2 Announce Type: replace Abstract: Cross-domain and cross-modal remote sensing image geo-localization remains challenging due to large appearance discrepancies and unstable semantic c

local-aiarxiv-cs-cv

SAGE: Ergodic Control for Autonomous and Adaptive Inspection of Subsea Infrastructure

arXiv:2608.19671v1 Announce Type: new Abstract: Subsea Christmas Trees (XTs) are underwater structures that use valves for directing oil flow, needing constant inspection. But not every valve carries

agentsarxiv-cs-ro

Applications

TT-net: Quantum Inspired Tensor Network Denoising in Conditional GANs

arXiv:2608.19789v1 Announce Type: new Abstract: Developed as a workhorse for classical simulations of quantum algorithms and quantum many-body systems, Tensor Network methods have entered the scientif

applicationsarxiv-cs-ai

Tutorials

What You Can't See Is What You Learn: Restricted Evidence Visibility Favors Compositional Generalization in Shared-Genome Language-Model Societies

arXiv:2608.20054v1 Announce Type: new Abstract: Multi-module systems often expose every module to the full input. We test whether restricting evidence visibility changes which solutions gradient-based

tutorialsarxiv-cs-ai

When Guidance Goes Off-Scale: Recalibrating Diffusion Transformers under Analog Compute-in-Memory Nonidealities

arXiv:2608.19644v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) incur high memory traffic and energy costs because sampling repeatedly evaluates large denoisers dominated by linear opera

Where Grounding Accuracy Lives on the IoU Curve: Label-Free Inference-Time Boundary Refinement

model-releasesarxiv-cs-cv

arXiv:2608.19553v1 Announce Type: new Abstract: Vision--language models can identify the correct referent while returning an imprecise bounding box. We study whether a frozen direct-answer model can u

YolovN-CBi: A Lightweight and Efficient Architecture for Real-Time Detection of Small UAVs

model-releasesarxiv-cs-cv

arXiv:2512.18046v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles, commonly known as, drones pose increasing risks in civilian and defense settings, demanding accurate and real-time drone d

ClosureBench: A Constructive Benchmark for Compositional Graph Reasoning

arXiv:2608.18242v1 Announce Type: new Abstract: We introduce ClosureBench, a constructive benchmark for compositional graph-relational reasoning with programmatically verified ground truth. Unlike fix

Hybrid Reinforcement Learning and Search for Flight Trajectory Planning

arXiv:2509.04100v3 Announce Type: replace Abstract: This paper explores the combination of Reinforcement Learning (RL) and search-based path planners to speed up the optimization of flight paths for a

agentsarxiv-cs-ai

Partition the Support, Reconstruct the Residual: Training-Free Sparse Attention for Video Generation and World Models

arXiv:2608.18484v1 Announce Type: cross Abstract: Training-free block-sparse attention can accelerate video transformers, but row-wise attention concentration does not by itself specify an executable

Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents

arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve.

safetyarxiv-cs-lg