Search: “reasoning”

arXiv:2604.20317v1 Announce Type: new Abstract: GAN-based facial attribute editing is widely used in virtual avatars and social media but often suffers from attribute entanglement, where modifying one

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Research

Object Referring-Guided Scanpath Prediction with Perception-Enhanced Vision-Language Models

DGX agent

arXiv:2604.20361v1 Announce Type: new Abstract: Object Referring-guided Scanpath Prediction (ORSP) aims to predict the human attention scanpath when they search for a specific target object in a visua

researcharxiv-cs-cv

23 Apr 2026

PLR: Plackett-Luce for Reordering In-Context Learning Examples

arXiv:2603.21373v2 Announce Type: replace-cross Abstract: In-context learning (ICL) adapts large language models by conditioning on a small set of ICL examples, avoiding costly parameter updates. Amon

PokeVLA: Empowering Pocket-Sized Vision-Language-Action Model with Comprehensive World Knowledge Guidance

model-releasesarxiv-cs-ro

arXiv:2604.20834v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have opened new avenues for robot manipulation, yet existing methods exhibit limited efficiency a

PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models

arXiv:2604.19773v1 Announce Type: cross Abstract: The construction of CAD models has traditionally relied on labor-intensive manual operations and specialized expertise. Recent advances in large langu

SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition

arXiv:2604.20146v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving

local-aiarxiv-cs-cl

Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs

arXiv:2512.08923v2 Announce Type: replace Abstract: We introduce two new benchmarks REST and REST+ (Render-Equivalence Stress Tests) to enable systematic evaluation of cross-modal inconsistency in mul

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models

arXiv:2604.19768v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic miscalibration with rhetorical intensity not proportionate to epistemic grounding. This study tests th

SGAP-Gaze: Scene Grid Attention Based Point-of-Gaze Estimation Network for Driver Gaze

model-releasesarxiv-cs-cv

arXiv:2604.19888v1 Announce Type: new Abstract: Driver gaze estimation is essential for understanding the driver's situational awareness of surrounding traffic. Existing gaze estimation models use dri

Stabilising Generative Models of Attitude Change

arXiv:2604.19791v1 Announce Type: new Abstract: Attitude change - the process by which individuals revise their evaluative stances - has been explained by a set of influential but competing verbal the

Applications

Stateless Decision Memory for Enterprise AI Agents

arXiv:2604.20158v1 Announce Type: new Abstract: Enterprise deployment of long-horizon decision agents in regulated domains (underwriting, claims adjudication, tax examination) is dominated by retrieva

applicationsarxiv-cs-ai

SweRank: Software Issue Localization with Code Ranking

arXiv:2505.07849v2 Announce Type: replace-cross Abstract: Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language

The Ratchet Effect in Silico through Interaction-Driven Cumulative Intelligence in Large Language Models

arXiv:2507.21166v2 Announce Type: replace-cross Abstract: Human intelligence scales through cumulative cultural evolution (CCE), a ratchet process in which innovations are retained against entropic dr

Thinking While Listening: Fast-Slow Recurrence for Long-Horizon Sequential Modeling

arXiv:2604.01577v2 Announce Type: replace-cross Abstract: We extend the recent latent recurrent modeling to sequential input streams. By interleaving fast, recurrent latent updates with self-organizat

To Know is to Construct: Schema-Constrained Generation for Agent Memory

arXiv:2604.20117v1 Announce Type: new Abstract: Constructivist epistemology argues that knowledge is actively constructed rather than passively copied. Despite the generative nature of Large Language

Treatment, evidence, imitation, and chat

arXiv:2506.23040v4 Announce Type: replace-cross Abstract: Large language models are thought to have the potential to aid in medical decision making. This work investigates the degree to which this mig

UniCon3R: Contact-aware 3D Human-Scene Reconstruction from Monocular Video

arXiv:2604.19923v1 Announce Type: new Abstract: We introduce UniCon3R (Unified Contact-aware 3D Reconstruction), a unified feed-forward framework for online human-scene 4D reconstruction from monocula

researcharxiv-cs-cv

Agents

A Self-Evolving Framework for Efficient Terminal Agents via Observational Context Compression

arXiv:2604.19572v1 Announce Type: new Abstract: As model capabilities advance, research has increasingly shifted toward long-horizon, multi-turn terminal-centric agentic tasks, where raw environment f

agentsarxiv-cs-cl

Accelerating trajectory optimization with Sobolev-trained diffusion policies

arXiv:2604.19011v1 Announce Type: new Abstract: Trajectory Optimization (TO) solvers exploit known system dynamics to compute locally optimal trajectories through iterative improvements. A downside is

local-aiarxiv-cs-lg

Hardware

ARGUS: Agentic GPU Optimization Guided by Data-Flow Invariants

arXiv:2604.18616v1 Announce Type: cross Abstract: LLM-based coding agents can generate functionally correct GPU kernels, yet their performance remains far below hand-optimized libraries on critical co

hardwarearxiv-cs-ai

Applications

Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models

arXiv:2604.18751v1 Announce Type: cross Abstract: Nonlinear machine-learning models are increasingly used to discover causal relationships in time-series data, yet the interpretation of their outputs

applicationsarxiv-cs-ai

Bridging Foundation Models and ASTM Metallurgical Standards for Automated Grain Size Estimation from Microscopy Images

model-releasesarxiv-cs-cv

arXiv:2604.18957v1 Announce Type: new Abstract: Extracting standardized metallurgical metrics from microscopy images remains challenging due to complex grain morphology and the data demands of supervi

Tutorials

ContextLeak: Auditing Leakage in Private In-Context Learning Methods

arXiv:2512.16059v2 Announce Type: replace-cross Abstract: In-Context Learning (ICL) has become a standard technique for adapting Large Language Models (LLMs) to specialized tasks by supplying task-spe

tutorialsarxiv-cs-cl

Counting Worlds Branching Time Semantics for post-hoc Bias Mitigation in generative AI

arXiv:2604.19431v1 Announce Type: cross Abstract: Generative AI systems are known to amplify biases present in their training data. While several inference-time mitigation strategies have been propose

safetyarxiv-cs-ai

CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers

arXiv:2604.19632v1 Announce Type: new Abstract: Graphic design images consist of multiple editable layers, such as text, background, and decorative elements, while most generative models produce raste

safetyarxiv-cs-cv

Cross-Model Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Across Three Large Language Models

arXiv:2604.19598v1 Announce Type: cross Abstract: This study compared repeated generation consistency of exercise prescription outputs across three large language models (LLMs), specifically GPT-4.1,

CulturALL: Benchmarking Multilingual and Multicultural Competence of LLMs on Grounded Tasks

arXiv:2604.19262v1 Announce Type: cross Abstract: Large language models (LLMs) are now deployed worldwide, inspiring a surge of benchmarks that measure their multilingual and multicultural abilities.

Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees

arXiv:2604.19000v1 Announce Type: cross Abstract: Statement autoformalization acts as a critical bridge between human mathematics and formal mathematics by translating natural language problems into f

Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean

arXiv:2604.19477v1 Announce Type: cross Abstract: The intonational structure of Seoul Korean has been defined with discrete tonal categories within the Autosegmental-Metrical model of intonational pho

Diff-SBSR: Learning Multimodal Feature-Enhanced Diffusion Models for Zero-Shot Sketch-Based 3D Shape Retrieval

arXiv:2604.19135v1 Announce Type: new Abstract: This paper presents the first exploration of text-to-image diffusion models for zero-shot sketch-based 3D shape retrieval (ZS-SBSR). Existing sketch-bas

safetyarxiv-cs-cv

DINO Eats CLIP: Adapting Beyond Knowns for Open-set 3D Object Retrieval

arXiv:2604.19432v1 Announce Type: new Abstract: Vision foundation models have shown great promise for open-set 3D object retrieval (3DOR) through efficient adaptation to multi-view images. Leveraging

safetyarxiv-cs-cv

Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey

arXiv:2603.04445v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) with diverse capabilities, costs, and domains has created a critical need for intelligent mod

Evaluating LLM-Driven Summarisation of Parliamentary Debates with Computational Argumentation

arXiv:2604.19331v1 Announce Type: new Abstract: Understanding how policy is debated and justified in parliament is a fundamental aspect of the democratic process. However, the volume and complexity of

safetyarxiv-cs-cl

EVPO: Explained Variance Policy Optimization for Adaptive Critic Utilization in LLM Post-Training

arXiv:2604.19485v1 Announce Type: cross Abstract: Reinforcement learning (RL) for LLM post-training faces a fundamental design choice: whether to use a learned critic as a baseline for policy optimiza

safetyarxiv-cs-ai

Experiments or Outcomes? Probing Scientific Feasibility in Large Language Models

arXiv:2604.18786v1 Announce Type: cross Abstract: Scientific feasibility assessment asks whether a claim is consistent with established knowledge and whether experimental evidence could support or ref

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling

model-releasesarxiv-cs-cv

arXiv:2509.12052v3 Announce Type: replace Abstract: Current talking-head generation has gradually shifted from GAN-based methods to diffusion-based paradigms, achieving remarkable progress in visual f

Agents

From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers

arXiv:2604.18652v1 Announce Type: cross Abstract: The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing o

agentsarxiv-cs-ai

Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI

arXiv:2604.19578v1 Announce Type: cross Abstract: With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of a

Inductive Subgraphs as Shortcuts: Causal Disentanglement for Heterophilic Graph Learning

arXiv:2604.19186v1 Announce Type: cross Abstract: Heterophily is a prevalent property of real-world graphs and is well known to impair the performance of homophilic Graph Neural Networks (GNNs). Prior

local-aiarxiv-cs-ai

Lost in Translation: Do LVLM Judges Generalize Across Languages?

arXiv:2604.19405v1 Announce Type: new Abstract: Automatic evaluators such as reward models play a central role in the alignment and evaluation of large vision-language models (LVLMs). Despite their gr

Agents

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization

arXiv:2506.09373v3 Announce Type: replace-cross Abstract: The advent of autonomous agents is transforming interactions with Graphical User Interfaces (GUIs) by employing natural language as a powerful

agentsarxiv-cs-ai

Mango: Multi-Agent Web Navigation via Global-View Optimization

arXiv:2604.18779v1 Announce Type: new Abstract: Existing web agents typically initiate exploration from the root URL, which is inefficient for complex websites with deep hierarchical structures. Witho

Mind the Unseen Mass: Unmasking LLM Hallucinations via Soft-Hybrid Alphabet Estimation

arXiv:2604.19162v1 Announce Type: new Abstract: This paper studies uncertainty quantification for large language models (LLMs) under black-box access, where only a small number of responses can be sam

Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge

arXiv:2603.11665v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have been widely adopted as MLLM-as-a-Judges due to their strong alignment with human judgment across vario

safetyarxiv-cs-cl

OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models

arXiv:2502.16161v2 Announce Type: replace-cross Abstract: Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understandin

OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models

arXiv:2604.00688v3 Announce Type: replace Abstract: We present OmniVoice, a massively multilingual zero-shot text-to-speech (TTS) model that scales to over 600 languages. At its core is a novel diffus

On Accelerating Grounded Code Development for Research

arXiv:2604.19022v1 Announce Type: new Abstract: A major challenge for niche scientific and technical domains in leveraging coding agents is the lack of access to up-to-date, domain- specific knowledge

On the Spatiotemporal Dynamics of Generalization in Neural Networks

arXiv:2602.01651v2 Announce Type: replace-cross Abstract: Why do neural networks fail to generalize addition from 16-digit to 32-digit numbers, while a child who learns the rule can apply it to arbitr

local-aiarxiv-cs-ai