Search: “inference”

Witness Overlap: Directional Provenance Inside Open-Weight Model Families

arXiv:2609.31784v2 Announce Type: replace Abstract: Open-weight models are often released, fine-tuned, aligned, merged, and re-released, making provenance audits ask not only whether checkpoints are r

16 Oct 2026

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Local Ai

Wolof-Adapted Industry-Ready Open-Weight Language Models

DGX agent

arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance

local-aiarxiv-cs-ai

16 Oct 2026

X-Fly: Learning to Reach and Stop in Full-Chunk Aerial Vision-Language Navigation

arXiv:2610.21450v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) agents built on large vision-language models are expensive to query. Executing a complete predicted action chu

safetyarxiv-cs-ai

16 Oct 2026

A Counterfactual Graph Approach to Oppositional Narrative Analysis

arXiv:2603.06135v3 Announce Type: replace-cross Abstract: Distinguishing legitimate critical speech from coordinated conspiracy narratives is a pressing challenge for the integrity of the online infor

Adaptive Computation with Conformal Certification

model-releasesarxiv-cs-lg

arXiv:2610.19189v1 Announce Type: new Abstract: Scientific imaging data involving medical (e.g., 3D radiographic, microscopic images) and astronomical sensors pose different challenges from natural im

Agents

Adaptive-Group Process Rewards for GUI Agents

arXiv:2610.17710v1 Announce Type: new Abstract: Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process

agentsarxiv-cs-ai

Anticipatory Evaluation of Language Models: Predicting LLM Benchmark Scores from Descriptions

model-releasesarxiv-cs-cl

arXiv:2509.20645v4 Announce Type: replace Abstract: Modern ML research increasingly faces an evaluation bottleneck: building benchmarks and running experiments is costly, slowing iteration. We ask how

Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration

arXiv:2610.14542v1 Announce Type: new Abstract: Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has re

Are We Overthinking One-Step Generation?

arXiv:2610.20331v1 Announce Type: new Abstract: Diffusion and flow matching are now dominant frameworks for generative modeling in continuous domains, but they typically require multiple network evalu

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

Back to the Future: Reverse-Consequence Modeling for Long-Horizon Particle Dynamics

arXiv:2610.18168v1 Announce Type: new Abstract: Accurate prediction of object trajectories is fundamental to mechanical understanding and robotic control. However, autoregressive models inherently suf

Budgeted KV-Cache Repair for Evolving Contexts

arXiv:2610.17338v1 Announce Type: new Abstract: Language-model agents revise their working context as information becomes obsolete, but deleting text does not erase its influence on cached computation

Applications

Chain of Time: In-Context Physical Simulation with Image Generation Models

arXiv:2511.00110v2 Announce Type: replace Abstract: We propose a novel cognitively-inspired prompting method to stabilize and interpret the physical simulation produced by autoregressive image generat

applicationsarxiv-cs-cv

Choosing the Number of Attention Heads from Intrinsic Dimension: A Small-Scale Study

arXiv:2610.19966v1 Announce Type: new Abstract: The number of attention heads in a transformer is usually set by convention or grid search. We test a simple heuristic for setting it in advance: estima

Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation

arXiv:2610.19141v1 Announce Type: new Abstract: Learning a collective policy for state-based Cartesian manipulation across diverse robotic embodiments presents a fundamental challenge due to embodimen

safetyarxiv-cs-ro

Comparative Evaluation of Deep-Learning based DoA Estimators for Real-Time ISAC Beamforming

arXiv:2610.20326v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) systems rely on accurate Direction-of-Arrival (DoA) estimation for effective beamforming and spectral-effici

Constitutive parameterized deep energy method for solid mechanics problems with random material parameters

model-releasesarxiv-cs-lg

arXiv:2603.26030v2 Announce Type: replace Abstract: In practical structural design and solid mechanics simulations, material properties inherently exhibit random variations within bounded intervals. H

Applications

Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

arXiv:2610.18991v1 Announce Type: new Abstract: Humanoid policies trained in simulation can transfer qualitatively to hardware while failing to transfer the force interactions learned during training,

applicationsarxiv-cs-ro

Copy-Paste Language Models

arXiv:2610.19247v1 Announce Type: new Abstract: Transformers are intuitively considered to be efficient at copying from their inputs. We actually show that the ability of LLMs to copy in context can b

Cross-Scenario Industrial Defect Detection via Domain-Robust Training and Metric-Aligned Selection

model-releasesarxiv-cs-cv

arXiv:2610.19540v1 Announce Type: new Abstract: Automated defect detection of industrial boards must remain highly reliable under cross-scenario variations in lighting, surface contaminants, and produ

CTIA-ODE: Continuous-Time Inter-Variable Attention for Long-Term Time Series Forecasting

arXiv:2610.19831v1 Announce Type: new Abstract: Although multivariate time series forecasting has broad application prospects, effectively incorporating exogenous variables remains challenging. Prevai

safetyarxiv-cs-lg

D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones

arXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-

DAGFormer: Global Topology Prediction for Transformer Cross-Layer Connections

arXiv:2610.19625v1 Announce Type: new Abstract: We propose DAGFormer, a Transformer language model whose cross-layer connections are planned by a jointly trained topology predictor. Beyond the residua

Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering

model-releasesarxiv-cs-cl

arXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand

Tutorials

Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

arXiv:2610.15692v2 Announce Type: replace Abstract: Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-ce

tutorialsarxiv-cs-cl

Do Syntax Heads Influence Model Behavior?

arXiv:2610.19231v1 Announce Type: new Abstract: Transformer language models develop attention heads that specialize in syntactic relations, for example, attending from verbs to their subjects. Do thes

Does the Explanation Drift Before the Guarantee? Label-Free Early Warning on Evolving Graphs

arXiv:2610.16534v1 Announce Type: new Abstract: Deployed models can fail silently as the world they describe evolves. Attribution drift has served as an early warning in tabular data; we ask whether,

Don't Run with Scissors: Pruning Breaks VLA Models but They Can Be Recovered

arXiv:2510.08464v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are a promising paradigm for field robotics, but their deployment is bottlenecked by strict edge SWaP-C co

safetyarxiv-cs-lg

Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility

model-releasesarxiv-cs-lg

arXiv:2606.15251v2 Announce Type: replace-cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential

End-to-End Vision-Language-Action Policies for Autonomous Lunar Rover Docking

arXiv:2610.19224v1 Announce Type: new Abstract: Surface navigation on the Moon is subject to extreme illumination contrast and deployment-time perceptual disturbances. While modular navigation pipelin

safetyarxiv-cs-ro

Energy-Based Models For Speech Synthesis

arXiv:2310.12765v2 Announce Type: replace-cross Abstract: Recently there has been a lot of interest in non-autoregressive (non-AR) models for speech synthesis, such as FastSpeech 2 and diffusion model

EPOCH: Coverage-Aware Evolution with Experiential Preference Optimization for LLM-based Automated Heuristic Design

arXiv:2610.17379v1 Announce Type: new Abstract: LLM-based automated heuristic design (AHD) discovers heuristics for combinatorial optimization problems (COPs), where an LLM generates candidates in an

Eval4DiRec: A Unified and Systematic Evaluation Framework for Diffusion-based Recommender Systems

arXiv:2609.34404v2 Announce Type: replace-cross Abstract: Leveraging the strong generative capabilities and stable training dynamics of diffusion models, diffusion-based recommender systems (RSs) have

Fewer Bits, More Tries: Recovering Capability Under Memory Constraints

arXiv:2610.15372v1 Announce Type: new Abstract: Large language models are generally more capable than smaller ones, but their memory requirements can make local deployment difficult. We ask whether pa

FlowSep-RF: Rectified Flow Matching for Single-Channel Radio-Frequency Signal Separation

arXiv:2610.20269v1 Announce Type: cross Abstract: Single-channel radio-frequency (RF) signal separation is important for interference mitigation when a signal of interest overlaps with a co-channel in

Local Ai

FPV-CRASH: A Dataset for Offline Crash Moment Localization in Drone First-Person-View Videos

arXiv:2610.19785v1 Announce Type: new Abstract: Crash Moment Localization aims to localize the major physical impact that interrupts controlled flight in an onboard first-person-view (FPV) video recor

local-aiarxiv-cs-cv

Frame Evidence:A Benchmark for Reference Frames and Visual Evidence in Multi-Image Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.19564v1 Announce Type: new Abstract: A spatial answer depends on the reference frame specified in language and its supporting visual evidence. Item accuracy alone obscures whether correctne

Framework for an AI-Ready ARPES Community Database

arXiv:2610.15236v1 Announce Type: cross Abstract: Condensed matter stands to gain profoundly from widespread adoption of artificial intelligence (AI). However, its current means of data organization i

From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring

arXiv:2610.19287v1 Announce Type: cross Abstract: Compute cost in automated essay scoring (AES) is usually treated as a technical efficiency issue rather than a measurement design concern. Yet deploym

Local Ai

From Plato to Aristotle: Toward a General Theory of Representation Hypotheses

arXiv:2610.20286v1 Announce Type: new Abstract: The Platonic Representation Hypothesis (PRH) holds that increasingly capable models converge toward a common representation. However, recent studies hav

local-aiarxiv-cs-lg

From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech

model-releasesarxiv-cs-cl

arXiv:2610.20370v1 Announce Type: new Abstract: Hate speech has become increasingly prevalent on social media, raising concerns about its detection, interpretation, and moderation. Persian, a relative

Frustratingly Easy Majority Voting Using Length Conditioning

arXiv:2610.19890v1 Announce Type: new Abstract: Majority Voting (MV) is a simple and widely used strategy which improves the reasoning accuracy of Large Language Models (LLMs) by allocating additional

safetyarxiv-cs-cl

Fully sequential Gaussian process regression for preference learning

arXiv:2610.19391v1 Announce Type: new Abstract: We study continuous global optimization problems in which the objective function cannot be directly evaluated; rather, we observe only which of two sele

safetyarxiv-cs-lg

Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents

arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source

Tutorials

GLoD-LVSM: Learning Geometry-Grounded Continuous-LoD Scene Representations for Large View Synthesis Models

arXiv:2610.20254v1 Announce Type: new Abstract: Large view synthesis models (LVSMs) reconstruct scenes from sparse views and render novel views quickly, but they incur unnecessary storage and renderin

tutorialsarxiv-cs-cv

HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation

arXiv:2610.19654v1 Announce Type: new Abstract: Simulated students let researchers test tutoring systems and teaching strategies before real learners are available, but only if the simulation reproduc

Harmony Harness: Multi-Objective Self-Evolution of Agent Harnesses

arXiv:2610.15150v1 Announce Type: new Abstract: Recent work on self-evolving LLM agents treats the agent harness as an optimization target that can be iteratively improved through execution feedback.

Applications

Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools

arXiv:2504.01627v2 Announce Type: replace-cross Abstract: Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces

applicationsarxiv-cs-ai