Search: “routing”

Overcoming Data Scarcity and Confidentiality in Hardware Assurance via Synthetic Generation

arXiv:2608.09914v1 Announce Type: cross Abstract: Hardware assurance relies on scanning electron microscopy (SEM) to verify nanoscale structures, but assembling the large, high-quality datasets requir

researcharxiv-cs-cv

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?

DGX agent

arXiv:2608.09629v1 Announce Type: new Abstract: Self-evolving agents are usually built around prescribed optimization pipelines: the framework decides how to gather evidence, revise a persistent artif

model-releasesarxiv-cs-ai

11 Aug 2026

Revision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines

arXiv:2604.01029v2 Announce Type: replace-cross Abstract: Multi-LLM revision pipelines, in which a second model reviews and improves a draft produced by a first, are widely assumed to derive their gai

RotaryQuant: Fitting 120B MoE Models on Consumer Hardware via Fused Compressed-Space Attention

model-releasesarxiv-cs-lg

arXiv:2608.08081v1 Announce Type: cross Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneo

SAIN: Structure-Aware Interactive Navigation with Active Dialogue Grounding for Mobile Robot

model-releasesarxiv-cs-ro

arXiv:2608.09196v1 Announce Type: new Abstract: Most existing vision-language navigation tasks assume that instructions are complete and unambiguous. However, real-world robots often encounter natural

Local Ai

Scale-to-Dialogue: Low-Burden Elicitation of Daily Premenstrual Symptom Ratings with Small Language Models

arXiv:2608.08746v1 Announce Type: new Abstract: Prospective daily symptom tracking is central to premenstrual health assessment, but repeated ordinal forms impose substantial response burden. We formu

local-aiarxiv-cs-ai

SLIM-0.5B: Learning Action-Grounded Predictive Latents for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.09771v1 Announce Type: new Abstract: Vision-language-action policies rely on large multimodal backbones to jointly perform perception, language conditioning, and action generation at every

SpikeWorld: Fast-State Adaptation for Frozen Spiking World Models

arXiv:2608.07712v1 Announce Type: cross Abstract: A predictive model receives a self-supervised signal whenever the consequence of an action is observed. Using that signal after deployment is difficul

Local Ai

SRE-FER: Regional residual evidence learning for mitigating local evidence dilution in fine-grained facial expression recognition

arXiv:2608.08702v1 Announce Type: new Abstract: Fine-grained facial expression recognition (FER) hinges on capturing subtle muscular cues that distinguish adjacent emotions. Yet capturing these cues p

local-aiarxiv-cs-cv

TeXFix-Bench: An Empirically Grounded Multi-Format Benchmark for LLM-Based Document Source Repair

arXiv:2608.07617v1 Announce Type: new Abstract: Scientific and technical writing depends on markup sources that must compile: LaTeX, Typst, and Markdown pipelines fail on missing delimiters, mismatche

The Knowing-Saying Gap: When Probes See Errors that Confidence Misses

arXiv:2608.07528v1 Announce Type: new Abstract: Linear probes detect corrupted context in language models with near-perfect accuracy, yet this does not translate into reliable failure prediction. The

The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World

arXiv:2608.08239v1 Announce Type: cross Abstract: LLM routers promise efficiency by matching each request to the cheapest adequate model, and are increasingly applied per step inside multi-step agents

agentsarxiv-cs-cl

Tied Trit-Planes: Constraining PTQTP to a Uniform Nine-Level Quantizer, with a Persistent Folded Format for Disk-Streamed Mixture-of-Experts Serving

model-releasesarxiv-cs-cl

arXiv:2608.08910v1 Announce Type: new Abstract: PTQTP decomposes LLM weight matrices into two ternary (trit) planes with two free per-group scales. Tying the scales to a fixed ratio of three collapses

TreeHop: Efficient Embedding-Level Query Rewriter

arXiv:2504.20114v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems face significant challenges in multi-hop question answering (MHQA), where complex queries require

Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation

arXiv:2608.09052v1 Announce Type: cross Abstract: Semi-supervised adaptation of vision foundation models (VFMs) commonly freezes the pretrained backbone and updates lightweight modules such as LoRA. H

World Tokens: Enhancing Embodied Policies with Training-Time World Modeling

arXiv:2608.09730v1 Announce Type: new Abstract: Vision-language-action (VLA) models are a widely adopted paradigm for embodied policies. They excel at efficient closed-loop control but do not explicit

safetyarxiv-cs-cv

Yesterday's Shield, Today's Spear: A Self-Evolving Safety Guardrail in Production

arXiv:2608.08471v1 Announce Type: new Abstract: Deployed LLM safety guardrails are predominantly static: trained once and frozen at release, while new jailbreak techniques and previously un-addressed

ZOMP: Zeroth-Order Multi-Modal Prompt Tuning for Vision-Language Models

arXiv:2608.08060v1 Announce Type: new Abstract: Fine-tuning vision-language models such as CLIP typically requires backpropagation (BP) through the full model, which is infeasible when only forward-pa

researcharxiv-cs-cv

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

arXiv:2608.06694v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is la

A Physics-Inspired Classical Digital Twin of Cortical Dynamics: A Band-Stratified Metriplectic Port-Hamiltonian Neural Network Learned from Brain-Computer-Interface EEG

arXiv:2607.10439v3 Announce Type: replace-cross Abstract: We present a physics-inspired classical digital twin of brain-computer- interface (BCI) data: a graph neural network constrained to a band-str

AgentPatch: Coarse-to-Fine Weak-Task Repair for Merging Agentic Multimodal Large Language Models

arXiv:2608.06699v1 Announce Type: new Abstract: Agentic multimodal large language models (MLLMs) extend multimodal perception and reasoning with planning, tool use, and interaction in dynamic environm

agentsarxiv-cs-ai

An End-to-End Agent Auditing Engine

arXiv:2608.07346v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of d

agentsarxiv-cs-ai

AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation

arXiv:2603.20986v2 Announce Type: replace Abstract: Phase-field modeling links thermodynamics and kinetics to microstructural evolution, but multiphysics frameworks such as MOOSE require expertise to

Beyond Text Matching: Towards Reference-Free Evaluation for Human-Oriented Binary Reverse Engineering

arXiv:2608.07038v1 Announce Type: cross Abstract: Human-Oriented Binary Reverse Engineering (HOBRE) aims to transform decompiled pseudocode into a more human-friendly representation, thereby reducing

Capek 0.5: An Execution-Centric Vision-Language Model for Embodied Intelligence

arXiv:2608.06756v1 Announce Type: new Abstract: Vision-language models are increasingly serving as the reasoning core of embodied agents. Robot execution is inherently iterative: each action reshapes

Debias in Text, Believe Your Eyes: Text-Anchored Cross-Modal Transfer for Visual Counter-Commonsense Reasoning

arXiv:2608.06938v1 Announce Type: cross Abstract: The visual reasoning ability of multimodal large language models (MLLMs) is crucial for downstream applications, particularly counter-commonsense reas

Diffusion LLMs as Targets and Adversaries: Mechanistic Safety Exploits

arXiv:2608.07430v1 Announce Type: cross Abstract: Diffusion Large Language Models (DLLMs) replace autoregressive next-token prediction with iterative parallel denoising, yet their internal safety mech

Local Ai

Evolving Parallel Algorithm Portfolios via Potential-Aware Instance Generation with LLMs

arXiv:2608.06808v1 Announce Type: new Abstract: The Automatic Construction of Portfolios via Large Language Models (LLM-ACP) suffers from poor generalization in practical few-shot scenarios when solvi

local-aiarxiv-cs-ai

FinRank: An Evidence-Grounded Benchmark for Financial Question Answering and Retrieval over SEC Filings

arXiv:2608.07400v1 Announce Type: new Abstract: Financial question answering is typically evaluated by answer correctness, yet in SEC filings a plausible and even numerically correct answer can be gro

Ising Acceleration for Multi-Robot Multi-Target Planning

arXiv:2608.06803v1 Announce Type: cross Abstract: Ising machines are emerging as promising hardware for combinatorial optimization. With recent advances in CMOS Ising technology, they are becoming att

researcharxiv-cs-ro

KReF: Training-Free Retrieval for Long-Term Time-Series Forecasting and Predictive Uncertainty

arXiv:2608.06748v1 Announce Type: cross Abstract: Probabilistic long-term time-series forecasting commonly relies on trained models. Training-free conformal methods typically construct intervals aroun

MotionStrata: Hierarchical Motion Latents for Compact Video Autoencoding

arXiv:2506.07136v2 Announce Type: replace Abstract: First-frame-conditioned video autoencoders represent a clip with persistent content and a compact motion code. Although this removes much of the app

researcharxiv-cs-cv

SimWAM: A Simple World Action Model for End-to-End Autonomous Driving

arXiv:2608.07468v1 Announce Type: new Abstract: World-Action Models (WAMs) improve end-to-end autonomous driving by transferring video dynamics priors to action prediction, but existing methods requir

agentsarxiv-cs-cv

Tutorials

Solver-Guided Reasoning for Mixed-Equilibrium Strategies

arXiv:2608.06741v1 Announce Type: new Abstract: Reasoning in large language models (LLMs) is often grounded in human text, human demonstrations, and human-generated rationales. For equilibrium reasoni

tutorialsarxiv-cs-lg

Adaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features

model-releasesarxiv-cs-ro

arXiv:2608.06008v1 Announce Type: new Abstract: Large video diffusion models provide rich spatiotemporal priors for autonomous driving, but existing world-action models often inherit the cost of itera

An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals

arXiv:2608.05255v1 Announce Type: cross Abstract: Retail investors lack access to the kind of personalized, tax-aware portfolio management that institutional clients take for granted -- existing robo-

DARAD: Dual Adapters and Ranking-Aware Distillation for Continual Remote Sensing Image-Text Retrieval

arXiv:2608.06059v1 Announce Type: new Abstract: With the rapid growth of Earth observation technologies, remote sensing archives are rapidly expanding, making remote sensing image-text retrieval (RS-I

safetyarxiv-cs-cv

Enhancing Social Intelligence in LLMs with Hierarchical Reasoning and Utterance-Level Goal Rewarding

model-releasesarxiv-cs-cl

arXiv:2608.05832v1 Announce Type: new Abstract: Large language models (LLMs) excel in structured tasks but struggle with dynamic social interactions, where success requires long-term goal coordination

Equipment-centric workpiece localization in near real-time using deep learning-based vision and event-driven finite state machines

arXiv:2608.05744v1 Announce Type: new Abstract: Continuous workpiece localization is essential for traceability and process coordination in hot forging, but direct tracking is unreliable because of ex

researcharxiv-cs-lg

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

arXiv:2608.06301v1 Announce Type: new Abstract: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts,

SemiAdapt-Instruct: Extensible Instruction Tuning via Latent Domain-Specialised Adapters

model-releasesarxiv-cs-cl

arXiv:2608.05161v1 Announce Type: new Abstract: Instruction-tuned LLMs are deployed into environments where domains evolve, yet extending a fine-tuned model's capabilities without full retraining rema

Applications

Sparse Mixture-of-Experts for Non-Uniform Noise Reduction in MRI Images

arXiv:2501.14198v3 Announce Type: replace-cross Abstract: Magnetic Resonance Imaging (MRI) is an essential diagnostic tool in clinical settings, but its utility is often hindered by noise artifacts in

applicationsarxiv-cs-cv

Verifiable Regularity Criterion for Conditional Expectation Operators and Conditional Mean Embeddings with Applications to Nonparametric Regression, Bayesian Inverse Problems, and Koopman Operators

arXiv:2608.06155v1 Announce Type: cross Abstract: Conditional expectation operators (CEOs) and their associated conditional mean embeddings (CMEs) play a central role across applied mathematics and ma

researcharxiv-cs-lg

When Do Prompt-Side Agent Playbooks Transfer? Accuracy, Cost, and Runtime Shift in Agent Deployment

arXiv:2608.05778v1 Announce Type: new Abstract: Prompt-side playbooks can improve tool-using language agents without retraining, but their portability beyond the source setting is unclear. We study fr

agentsarxiv-cs-ai

Capability-Gated Planning: Cost-to-Goal Discovery and the Limits of Myopic Experiment Selection

arXiv:2608.05085v1 Announce Type: cross Abstract: Systems that automate scientific discovery must repeatedly decide which experiment to run, which hypothesis to test, which tool to build, and when to

COMPAS: Difficulty-Aware Joint Search for Optimizing Code Generation

arXiv:2608.04336v1 Announce Type: cross Abstract: Code generation systems make each LLM call with a model, a prompt, and decoding settings. However, existing optimization methods usually tune only par

Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations

model-releasesarxiv-cs-lg

arXiv:2608.04778v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) incorporate governing equations into neural-network training and can approximate PDE solutions without requirin

Diverse and Plausible Algorithmic Recourse via Tractable Recourse Distributions

model-releasesarxiv-cs-lg

arXiv:2608.04677v1 Announce Type: new Abstract: Algorithmic recourse seeks to help individuals reverse unfavorable automated decisions by recommending actionable changes that achieve a desired outcome