Search: “routing”

DelegationBench: Measuring When AI Agents Should Ask Before Acting

model-releasesarxiv-cs-lg

arXiv:2610.05532v1 Announce Type: cross Abstract: AI agents that send emails, edit files, and make purchases must decide when to act on their own and when to check with the user first. This decision i

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Disentangling Task Difficulty from Run-Level Failure in Agent Failure Prediction

DGX agent

arXiv:2610.05572v1 Announce Type: new Abstract: Predicting whether an LLM agent will fail has emerged as a promising direction for supporting intervention during execution. Recent approaches report st

model-releasesarxiv-cs-lg

6 Oct 2026

Tutorials

DiVeR: Decision-Critical Verifier Learning for VLA Test-Time Scaling

arXiv:2610.04933v1 Announce Type: cross Abstract: Scaling robot data and model capacity has improved Vision-Language-Action (VLA) policies, but further progress is constrained by the high cost of robo

tutorialsarxiv-cs-lg

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

model-releasesarxiv-cs-lg

arXiv:2610.04137v1 Announce Type: new Abstract: Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Be

Applications

From Abusive Language Classification to Sequence Labeling Identification

arXiv:2610.06287v1 Announce Type: cross Abstract: Industrial content moderation must process massive message streams under tight latency constraints, yet most abusive language (AL) detection systems r

applicationsarxiv-cs-lg

Hardware

Frozen Factor or Spectral Band? Disentangling Two Choices in Low-Rank LoRA

arXiv:2610.06621v1 Announce Type: new Abstract: Spectral variants of low-rank adaptation (LoRA) choose both a subspace and which factor to freeze. We separate these choices by freezing the input facto

hardwarearxiv-cs-lg

Learning to Read the Contextual Tokens in Diffusion Transformers

arXiv:2610.06844v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) jointly process visual and textual representations throughout generation. These models repeatedly update the

safetyarxiv-cs-cv

Agents

Managed Apache Iceberg at scale: How Spanner powers Lakehouse runtime catalog

As customers modernize to lakehouse architectures, they are standardizing on open formats such as Apache Iceberg to create a shared data estate across compatible engines. This enables you to build AI-

agentsgoogle-cloud-ai

MeSD: Multi-Evidence Self-Distillation for VideoLLM

arXiv:2610.06342v1 Announce Type: new Abstract: While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-lev

safetyarxiv-cs-cv

Organize Primitives into Semantic Parts: Reinforcement Reasoning for 3D Segmentation

arXiv:2610.04602v1 Announce Type: new Abstract: Primitive-based 3D segmentation offers a compact and explicit alternative to dense surface prediction, naturally supporting structural abstraction and b

local-aiarxiv-cs-cv

ReMAP: Restoring the Perceptual Cycle with Reasoning-Time Latent Visual Memory

model-releasesarxiv-cs-cv

arXiv:2610.05097v1 Announce Type: new Abstract: As multimodal large language models (MLLMs) reason for longer, attention to the initial visual input diminishes, weakening visual grounding. Visual memo

RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices

arXiv:2610.04784v1 Announce Type: cross Abstract: Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energ

local-aiarxiv-cs-lg

RSure-Agent: Reliable Use of Tool Observations for Remote Sensing Agents

model-releasesarxiv-cs-cv

arXiv:2610.04836v1 Announce Type: new Abstract: Remote sensing agents rely on perception, measurement, and raster analysis tools to solve Earth observation tasks. We refer to their judgments and quant

Towards Subject-Oriented Video Captioning via User-Specified Targets

arXiv:2312.13330v3 Announce Type: replace Abstract: Describing video content according to users' needs is a long-held goal. Although existing video captioning methods have made significant progress, t

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

Voltic: Distinguishing Volatility from Stochasticity in Recurrent Memory

model-releasesarxiv-cs-lg

arXiv:2610.05700v1 Announce Type: new Abstract: Recurrent sequence models must decide how strongly to overwrite their memory at each token. Read as Bayesian filtering, this write is the gain of a Kalm

Agents

When Debate Helps: Proposal Supply and Verification-Aware Readout in Multi-Agent Reasoning

arXiv:2610.04686v1 Announce Type: cross Abstract: Multi-agent debate can improve reasoning, yet often fails to beat simple majority voting. We argue that successful debate requires two distinct mechan

agentsarxiv-cs-lg

AvoKV-E: Payload-Aware KV Cache Eviction for Long Reasoning

arXiv:2610.03007v1 Announce Type: cross Abstract: Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely t

Awomo-SimDataEngine: Agentic Simulation-ReadyWorld Generation

arXiv:2610.02274v1 Announce Type: new Abstract: Generating useful robot-training data requires more than visually plausiblescenes: objects must support interaction, placements must remain physicallyva

safetyarxiv-cs-ro

BeeWhere: Segmenting Bumble Bee Colonies to Quantify Behavioral Effects

arXiv:2610.03051v1 Announce Type: new Abstract: Social bees are important pollinators that support biodiversity and crop pollination globally and serve as important model systems for collective behavi

Budgeted Cache Repair for Cross-Context KV-Cache Reuse

arXiv:2610.02233v1 Announce Type: cross Abstract: Cross-context KV-cache reuse predicts a shared segment's keys and values under a new prefix instead of recomputing them, and has been reported to do s

Capability Scaling-Down Laws for LLM Compression

arXiv:2610.02462v1 Announce Type: cross Abstract: LLM compression reduces inference costs and memory requirements, but selecting a method and configuration remains largely empirical because comparable

Custom Forcing: Training-Free Subject Customization for Autoregressive Video Generation

arXiv:2610.02914v1 Announce Type: new Abstract: Autoregressive video models can generate minute-long videos in real time, but they produce generic subjects from text rather than specific subjects from

EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning

local-aiarxiv-cs-ai

FSPO: Policy-Consistent Risk and Pareto-Feasible Control for Budgeted LLM RL Post-Training

arXiv:2610.02828v1 Announce Type: new Abstract: Adaptive LLM reinforcement-learning post-training changes multiple training actuators online, including rollout temperature, group size, clipping, KL re

How Robust Is Multimodal Claim Verification to LLM Rewriting?

arXiv:2610.02841v1 Announce Type: new Abstract: LLMs are known to introduce stylistic changes into generated text, yet how these stylistic shifts affect model decisions on scientific tasks remains und

Information Limits of Low-Rank Approximation Certification

arXiv:2610.03321v1 Announce Type: cross Abstract: Low-rank approximation can require additional matrix--vector products to verify that its error meets a prescribed tolerance. We characterize this cert

researcharxiv-cs-ai

IntentCoding: Amplifying User Intent in Code Generation

model-releasesarxiv-cs-ai

arXiv:2602.00066v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong capabilities in code generation, but their adherence to fine-grained user intent with multiple constrai

Labels Override Definitions in Jev-Style Typed Decision Models

arXiv:2610.02586v1 Announce Type: new Abstract: A typed decision model answers a fixed question about an input by returning a probability for each of several caller-defined options. Each option carrie

Lexicographic Multi-Objective On-Policy Distillation

arXiv:2610.02359v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards (RLVR) usually optimizes answer correctness, yet useful language-model behavior also requires high-qual

Agents

LLM-Guided Reinforcement Learning with Representative Agents for Traffic Modeling

arXiv:2511.06260v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as behavioral proxies for self-interested travelers in agent-based traffic models. Although

agentsarxiv-cs-ai

Multilingual GSM-Symbolic: What determines capability transfer across languages?

arXiv:2610.03367v1 Announce Type: new Abstract: We understand little about how capabilities acquired in one language carry over to another, or what governs this transfer: evaluations rely on incompara

researcharxiv-cs-ai

Online Verification of Language Model Responses Under Cost Constraints

arXiv:2610.02632v1 Announce Type: new Abstract: As large language models are increasingly deployed for multi-step reasoning, verifying the correctness of their outputs has become essential for maintai

safetyarxiv-cs-lg

Preserving Mathematical Reasoning in Compressed Diffusion Language Models via Trajectory-Aware Low-Rank Approximation

arXiv:2610.03326v1 Announce Type: new Abstract: Diffusion language model (dLLM) compression faces a known challenge because calibration is typically performed on clean, fully visible activations, wher

researcharxiv-cs-ai

SEDIMA: Cross-Run Hierarchical Insight Memory for Evolutionary Search Agents

arXiv:2610.02361v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are l

The Shape of Speech: A Geometric Measure of Coarticulation for Speech-Driven 3D Facial Animation

arXiv:2610.03436v1 Announce Type: cross Abstract: Speech-driven 3D facial animation can reproduce recognizable mouth poses. However, it can simplify the motion between them, and that motion carries co

safetyarxiv-cs-cv

TRAC: Trajectory-aware Reuse and Adaptive Correction for Efficient Autoregressive Video Generation

arXiv:2610.02779v1 Announce Type: new Abstract: In this paper, we present trajectory-aware reuse and adaptive correction (TRAC), a training-free framework for efficient autoregressive (AR) video gener

WakeKV: Reactive, Reversible KV Residency for Heads That Change Their Minds

model-releasesarxiv-cs-cl

arXiv:2610.02713v1 Announce Type: new Abstract: Most KV-cache compression methods classify attention heads once, either offline or during prefill, and keep this classification fixed throughout generat

Syntheses

Wiki Lint Report — 2026-10-04

linthealth-checkautomated

Automated lint: 19 errors, 64915 warnings, 3 info

4 Oct 2026

poorman inference engine for 16GB GPU and 35B moe Qwen 3.6for coding

model-releasesr-localllama

I forked llama.cpp's server into AgrillaMoE, a dedicated build for Qwen3.6-35B-A3B (~A4B) with Unsloth quants. On a (vant.ai) rented V100 16GB with the 2-bit UD-Q2_K_XL quant it generates at ~57-60 to

4 Oct 2026

b11374

model-releasesllama-cpp-releases

ggml-openvino: update to 2026.4.1, optimize performance, expand ops, improve device listing. (#29852) ggml-openvino : Qwen3.5 MoE perf (#312) Squash of ravi9#312: ggml-openvino: add detailed inference

3 Oct 2026

ollama pull clef open models for all. start building with @ollama and @cloudflare clef decision models today

ollama pull clef open models for all. start building with @ollama and @cloudflare clef decision models today .@Cloudflare's decision models are available on Ollama! Decision models allow you to classi

local-aiollama--x

3 Oct 2026

Context-Aware Error Mitigation Orchestration for Hybrid Quantum Reinforcement Learning on NISQ Systems

arXiv:2610.01253v1 Announce Type: new Abstract: Quantum Reinforcement Learning (QRL) integrates reinforcement learning with parameterized quantum circuits and is a promising approach to combinatorial

safetyarxiv-cs-lg

Emergent Unfaithfulness: How Alignment Training Causes Language Models to Silently Override Task Faithfulness

arXiv:2610.00568v1 Announce Type: cross Abstract: Large language models are characterized by three key properties: capability, alignment, and faithfulness. Prior work studies the tradeoffs between cap

Hardware

Fast Polynomial Transcendentals for LLMs

arXiv:2610.00049v1 Announce Type: new Abstract: Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardwa

hardwarearxiv-cs-lg

FFBL-Coop: Association-Decoupled Cooperative 3D Multi-Object Tracking

model-releasesarxiv-cs-cv

arXiv:2610.01750v1 Announce Type: new Abstract: Cooperative 3D tracking must integrate complementary observations across agents and time while maintaining consistent identities. When evidence integrat

Latent-Foresight: End-to-End Learning Predictable Representations for Latent World Models

arXiv:2610.01942v1 Announce Type: new Abstract: Predicting the future evolution of a scene is a fundamental capability for world modeling. Recent work has shown that operating in the feature space of

Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon

arXiv:2610.00422v1 Announce Type: cross Abstract: Neural combinatorial optimization typically assumes a centralized solver that reads the whole instance. We study the opposite: combinatorial optimizat

local-aiarxiv-cs-ai