Search: “routing”

First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on f

local-aiarxiv-cs-lg

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory

DGX agent

arXiv:2607.27919v1 Announce Type: new Abstract: Decoder-only language models entangle long-term memory and reasoning in a single parameter set, making it difficult to scale memory capacity independent

model-releasesarxiv-cs-cl

31 Jul 2026

Tutorials

MentorCollab: Selective Large-to-Small Inference-Time Guidance for Efficient Reasoning

arXiv:2602.05307v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve strong performance by producing long chains of thought, but their inference costs are high and often generate

tutorialsarxiv-cs-cl

One Patch Is Enough: Reinforcement-Optimized Visual Token Grounding for MLLM-Based Scene Text Spotting

model-releasesarxiv-cs-cv

arXiv:2607.27902v1 Announce Type: new Abstract: Scene text spotting requires high-precision alignment between textual recognition and spatial localization. While visual-token grounding has emerged as

Policy Gradient Steering: Interventions from Behavioral Objectives

arXiv:2607.27574v1 Announce Type: new Abstract: Activation steering has emerged in large language models as a lightweight alternative for dynamically changing a model's behavior at inference time. How

safetyarxiv-cs-lg

Reasoning Consensus: Structural Ensembling of LLM Reasoning via Weighted DAG Aggregation

arXiv:2607.27783v1 Announce Type: new Abstract: Large Language Models (LLMs) explore problems through chain-of-thought, but this exploration is buried in unstructured prose. On high-stakes tasks, user

researcharxiv-cs-cl

SkillSight: Calibrating Generic Content Bias for Skill Retrieval

arXiv:2607.18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability

VCP-DCN: Beyond Visual Concealed Property via Depth Collaborative Network for Camouflaged Object Detection

arXiv:2607.27843v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to identify and segment camouflaged objects in complex environments, which are often concealed because their col

local-aiarxiv-cs-cv

Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees

model-releasesarxiv-cs-lg

arXiv:2607.28399v1 Announce Type: new Abstract: Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed. We ide

FedWeave: Rethinking the Unit of Specialization in Heterogeneous Federated MoE-LoRA

arXiv:2607.26618v1 Announce Type: cross Abstract: Federated PEFT enables LLMs to collaboratively adapt to decentralized private data without sharing raw examples. However, task heterogeneity across cl

Lottery Tickets Are Not Deployment Tickets

arXiv:2607.27031v1 Announce Type: cross Abstract: Reports on how sparsification, compression, and lottery tickets change model behavior have been mixed in the prior literature, with beneficial effects

safetyarxiv-cs-cv

MedARC: Training-Free Adaptive Redundancy Compression of Visual Tokens for 3D Medical Vision-Language Models

arXiv:2607.26554v1 Announce Type: new Abstract: Integrating 3D medical images with vision-language models (VLMs) holds substantial promise for computer-aided diagnosis. However, volumetric images gene

local-aiarxiv-cs-cv

Misalignment Has a Personality: A Big Five Account of Emergent Misalignment

arXiv:2607.26389v1 Announce Type: new Abstract: Fine-tuning a language model on data containing a narrow flaw, such as insecure code or incorrect mathematical answers, can cause broad misalignment thr

safetyarxiv-cs-cl

Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification

arXiv:2607.26565v1 Announce Type: new Abstract: Vision models do not form a representation at once; each block revises it. We ask whether the resulting computation path contains evidence that the fina

researcharxiv-cs-cv

Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation

arXiv:2607.26599v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects is central to targeted interventions, such as personalized promotions and precision medicine. We focus on the

local-aiarxiv-cs-lg

Beyond Self-Knowledge: Propagating Uncertainty Across Reasoning and Retrieval in LLMs

arXiv:2607.25600v1 Announce Type: cross Abstract: Retrieval-augmented generation improves knowledge-intensive question answering, but indiscriminate retrieval can introduce irrelevant evidence and unn

29 Jul 2026

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning

arXiv:2607.18060v2 Announce Type: replace Abstract: Long-horizon robotic tasks require diverse capabilities that no single policy can reliably provide. Heterogeneous policies offer complementary stren

safetyarxiv-cs-ro

29 Jul 2026

Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm

arXiv:2607.25446v1 Announce Type: new Abstract: Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), ho

29 Jul 2026

CausalGate: Causal Importance Distillation for Transformer Module Pruning

arXiv:2607.22720v1 Announce Type: cross Abstract: Existing adaptive inference methods for Large Language Models rely on observational heuristics, such as hidden-state similarity or activation magnitud

Cheap Probes Predict Expensive Training in 3D-CT Vision--Language Models

arXiv:2607.22771v1 Announce Type: cross Abstract: Picking the frozen image encoder for a 3D~CT vision--language model (VLM), together with the token-compression scheme on top of it, is a search over m

Applications

Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification

arXiv:2607.24683v1 Announce Type: cross Abstract: Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance. However, real-world scen

applicationsarxiv-cs-ai

Do Visual Features Improve Other-Initiated Repair Detection? A Dyadic Multimodal Approach

arXiv:2607.23845v1 Announce Type: new Abstract: Other-initiated Self-repair, or in short Other-initiated Repair (OIR), is an essential mechanism in conversational interaction, whereby a recipient sign

researcharxiv-cs-ai

DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference

arXiv:2607.24434v1 Announce Type: cross Abstract: Large Mixture-of-Experts (MoE) language models are attractive for end-device deployment because only a small subset of experts is active per token, bu

DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection

arXiv:2607.23924v1 Announce Type: cross Abstract: Vision foundation models have enabled strong training-free anomaly detection (AD). However, most existing approaches rely primarily on independent loc

GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models

arXiv:2607.23913v1 Announce Type: new Abstract: Modern vision-language models (VLMs) increasingly rely on dynamic or high-resolution visual encoding, producing thousands of visual tokens that substant

HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization

arXiv:2607.22578v1 Announce Type: new Abstract: The proliferation of Large Language Models (LLMs) has shifted serving systems from processing isolated requests to orchestrating high-concurrency, multi

Joint Optimization for Greedy Longest-match Tokenization

arXiv:2607.23362v1 Announce Type: new Abstract: Recent work has shown that subword vocabularies can be trained to optimize compression for a specific inference rule rather than relying on greedy heuri

researcharxiv-cs-cl

Kimi K3: Open Frontier Intelligence

arXiv:2607.24653v1 Announce Type: new Abstract: We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token

Agents

Learning Traversability-Aware Global Planners for Long Horizon Off-Road Navigation

arXiv:2607.23743v1 Announce Type: new Abstract: Autonomous navigation across large off-road environments remains a challenging problem. Onboard sensors perceive only the immediate surroundings, yet sa

agentsarxiv-cs-ro

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition

arXiv:2607.24030v1 Announce Type: new Abstract: Massively multilingual automatic speech recognition (ASR) models covering hundreds of languages must maintain robust performance across diverse linguist

MSVS-VAE: Multi-Scale Anchored VecSet for High-Fidelity 3D Reconstruction

arXiv:2607.24436v1 Announce Type: new Abstract: High-fidelity 3D generative modeling increasingly relies on the latent diffusion paradigm, where the reconstruction quality of the underlying 3D VAE bec

researcharxiv-cs-cv

Hardware

Omni-Prune: Query-Aware Unified Token Pruning for Efficient Omnimodal Large Language Models

arXiv:2607.23445v1 Announce Type: cross Abstract: Omnimodal large language models (OmniLLMs) are rapidly extending multimodal reasoning to cover synchronized audio and video. However, the resulting au

hardwarearxiv-cs-cl

Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary

arXiv:2607.18553v2 Announce Type: replace-cross Abstract: Can a language model read the quality of its ongoing computation, and can an external intervention turn that readout into better outcomes? We

researcharxiv-cs-ai

Tutorials

PathSelect: Sequential Token Selection for Whole Slide Pathology

arXiv:2607.23631v1 Announce Type: new Abstract: Gigapixel Whole-Slide Images (WSIs) present a fundamental computational bottleneck for vision-language models (VLMs) due to extreme sequence lengths. Ex

tutorialsarxiv-cs-cv

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention

arXiv:2607.24593v1 Announce Type: new Abstract: Token-level sparse attention, as implemented by DeepSeek Sparse Attention (DSA) in production systems, makes the downstream attention efficient but shif

ProvenanceGuard: Source-Aware Factuality Verification for MCP-Based LLM Agents

arXiv:2606.18037v2 Announce Type: replace Abstract: Tool-using LLM agents increasingly use the Model Context Protocol (MCP) to answer from heterogeneous evidence sources, including search, APIs, datab

PTStore (Prefix Tensor Store): Distributed Prefix Caching and Replication for High Throughput Inference Serving

arXiv:2607.22648v1 Announce Type: new Abstract: Inspired by the design of client caching in Content Delivery Networks (CDNs), PTStore distributes and replicates popular tensors that form reusable KV c

researcharxiv-cs-ai

Sheaf-Laplacian Obstruction and Projection Hardness for Cross-Modal Compatibility on a Modality-Independent Site

arXiv:2604.07632v2 Announce Type: replace-cross Abstract: Cross-modal representations vary in how easily they can be aligned, and compatibility is generally non-transitive: two modalities may align th

Hardware

Small-Pollinator Detection in Cluttered Field Video

arXiv:2607.22913v1 Announce Type: new Abstract: Detecting pollinators in field video is challenging: targets are small, visually similar, and observed against cluttered vegetation under blur and occlu

hardwarearxiv-cs-cv

Spectral Dynamics of Semantic Drift in Clinical Multi-Agent Language Model Networks

arXiv:2607.22758v1 Announce Type: cross Abstract: The integration of iterative LLMs within multi-agent diagnostic frameworks requires a rigorous quantitative reevaluation of underlying communication t

The Cross-Domain Generalization Cost of Offensive Language Detection

arXiv:2607.23512v1 Announce Type: new Abstract: Offensive language detection models generally suffer performance degradation when deployed across datasets and across languages, yet most existing studi

researcharxiv-cs-cl

TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation

arXiv:2607.23838v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) lets a large language model answer questions using documents retrieved from an external knowledge base at query t

When Can Depth Replace Precision? A Resource Theory of Quantized Neural Computation

arXiv:2607.23390v1 Announce Type: new Abstract: When can additional low-bit residual computation replace missing numerical precision for a fixed input-output map? We model a quantized residual system

researcharxiv-cs-lg

Agents

Multi-Agent Debate and Visual Information Extraction for SeePhys Pro: A 1st-Place Technical Report from ICML 2026 AI4Math Track 3 Challenge

arXiv:2607.21946v1 Announce Type: new Abstract: This technical report presents our approach to Challenge Track~3: SeePhys Pro at the 3rd AI for Math Workshop, where the task is to answer college-level

agentsarxiv-cs-lg

SwiftMem: Fast Agentic Memory via Query-aware Indexing

arXiv:2601.08160v2 Announce Type: replace Abstract: Agentic memory systems have become critical for enabling LLM agents to maintain long-term context and retrieve relevant information efficiently. How

Applications

Token-Operations-Oriented Inference Optimization Techniques for Large Models

arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode

applicationsarxiv-cs-cl

Twins: Learn to Predict Unified Representations with Focal Loss

arXiv:2607.22531v1 Announce Type: new Abstract: Unified multimodal models seek a shared visual token space that supports both multimodal understanding and image generation. Discrete methods unify the

safetyarxiv-cs-cv

EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization

arXiv:2607.21013v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved impressive performance in multimodal emotion recognition (MER) tasks and lifted MER to a new leve