Search: “reasoning”

JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks

arXiv:2602.06486v4 Announce Type: replace Abstract: Evaluating agentic AI on open-ended professional tasks faces a fundamental dilemma between rigor and flexibility. Static rubrics provide rigorous, r

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Model Releases

Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

DGX agent

arXiv:2607.12924v1 Announce Type: new Abstract: In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic acti

model-releasesarxiv-cs-ai

15 Jul 2026

Knowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language Modeling

arXiv:2607.12831v1 Announce Type: new Abstract: Language models encode substantial factual knowledge in their parameters, which can lead to unreliable behavior when this knowledge is outdated, incompl

researcharxiv-cs-cl

Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts

arXiv:2607.12696v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) models have become an important approach for scaling Large Language Models (LLMs), but their inference efficiency depe

Look, Focus, Act: Efficient and Robust Robot Learning via Human Gaze and Foveated Vision Transformers

arXiv:2507.15833v3 Announce Type: replace-cross Abstract: Human vision is a highly active process driven by gaze, which directs attention to task-relevant regions through foveation, dramatically reduc

Mirror Horizon: Viable Path Entropy as a Measure of Bounded Reflection

model-releasesarxiv-cs-lg

arXiv:2607.11937v1 Announce Type: new Abstract: Mirror Theory proposes that an intelligent system should be studied not only by what it represents, but by what coherent continuations it can sustain un

More Than Where You Are: Learning Semantics, Structure, and Geometry from Cross-View Localization

arXiv:2607.12429v1 Announce Type: new Abstract: Consistent cross-view understanding under extreme viewpoint changes is essential for spatial intelligence, as it enables models to recognize the same sc

local-aiarxiv-cs-cv

OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes

arXiv:2607.11896v1 Announce Type: cross Abstract: Forecasting particulate matter (PM10) requires both station-scale accuracy and continuous spatial fields, especially during severe dust storms. Chemic

local-aiarxiv-cs-ai

Policy-Conditioned Constrained Decoding for Column-Level Access Control in Text-to-SQL

arXiv:2607.12341v1 Announce Type: new Abstract: Text-to-SQL is increasingly deployed across trust boundaries between data providers and users. Such deployment must balance three competing requirements

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Tutorials

QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design

arXiv:2607.11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in com

tutorialsarxiv-cs-ai

Rough Path Signature-Guided Geometry Augmentation for Few-Shot Industrial Surface Defect Detection

arXiv:2607.12245v1 Announce Type: new Abstract: Few-shot industrial defect detection remains difficult for standard supervised detectors, which achieve poor performance on boundary-dominated industria

Saturation Makes Quantization Error Additive: A Coverage Model with a Certificate

arXiv:2607.12266v1 Announce Type: new Abstract: Mixed-precision quantization must decide which parts of a model to keep at higher precision. A common premise, shared by sensitivity-based methods such

researcharxiv-cs-lg

Scaling Point-in-Time Language Models

arXiv:2607.11889v1 Announce Type: cross Abstract: Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromis

So Many Opinions, So Many LLMs: Comparing Large Language Models to Traditional Machine Learning for Open- Ended Survey Analysis

arXiv:2607.11890v1 Announce Type: cross Abstract: Open-ended surveys offer valuable insights, but they are notoriously difficult to analyze at scale. Building on previous work that employed traditiona

StratMamba: Strategic and Reactive Stream Partitioning for Path-Efficient LiDAR-Based Obstacle Avoidance

arXiv:2607.12370v1 Announce Type: new Abstract: This paper proposes StratMamba, a dual-stream Mamba-based temporal modeling architecture, to more efficiently capture long-horizon temporal dependencies

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SymbOmni: Evolving Agentic Omni Models via Symbolic Concept Learning

arXiv:2607.12042v1 Announce Type: new Abstract: Visual generation is increasingly ubiquitous in diverse domains, from text-to-image/video synthesis to multimodal interactive creation. Yet prevailing m

agentsarxiv-cs-cv

TAKE: Trajectory-Aware Knowledge Estimation for Text Dataset Distillation

arXiv:2607.11898v1 Announce Type: new Abstract: Large-scale text corpora have become a quiet bottleneck in modern NLP, not just in storage, but in the accumulated cost of training, fine-tuning, and co

researcharxiv-cs-cl

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

arXiv:2405.11667v2 Announce Type: replace Abstract: Local SGD is a popular optimization method in distributed learning, often outperforming other algorithms in practice, including mini-batch SGD. Desp

researcharxiv-cs-lg

The Seriality Gap in Video Diffusion Models

arXiv:2607.13031v1 Announce Type: cross Abstract: When one ball strikes another, then another, video models should predict the consequences of each bounce. In controlled experiments on multi-ball hard

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

arXiv:2607.12113v1 Announce Type: cross Abstract: One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around fi

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Towards Self-Evolving Agents: A Human-Inspired Adaptive Exploration-Exploitation Framework for Genetic Network Programming

arXiv:2607.11913v1 Announce Type: cross Abstract: Recent advancements in agentic AI have increasingly moved toward graph-based methods, driven by the demand for explainable, human-centered, and non-li

ViHoRec: A Quality-Controlled Vietnamese Hotel Recommendation Dataset and Cold-Start Benchmark

arXiv:2607.12946v1 Announce Type: cross Abstract: Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a res

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary

arXiv:2607.11953v1 Announce Type: new Abstract: Does a reinforcement-learning agent that earns high reward represent its task's latent state, or only a reward-correlated shortcut? The question is usua

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Beware What You Autocomplete: Forensic Attribution of Backdoored Code Completions

arXiv:2607.08011v1 Announce Type: cross Abstract: Large language models have enabled powerful code completion systems that assist developers by predicting subsequent lines of code. However, these mode

Cognitive-structured Multimodal Agent for Multimodal Understanding, Generation, and Editing

arXiv:2607.08497v1 Announce Type: cross Abstract: Recent unified multimodal models show a single architecture can jointly perform vision/language understanding and image generation/editing. However, t

Applications

Conversational AI for Rapid Scientific Prototyping: A Case Study on ESA's ELOPE Competition

arXiv:2601.04920v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as coding partners, yet their role in accelerating scientific discovery remains underexplored. Th

applicationsarxiv-cs-ai

DR-Arena: an Automated Evaluation Framework for Deep Research Agents

arXiv:2601.10504v2 Announce Type: replace Abstract: As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, rel

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From Legacy Documentation to OSCAL: An MCP-Based Agent Pipeline for Threat-Informed Continuous Compliance in Critical Infrastructure

arXiv:2607.08288v1 Announce Type: cross Abstract: In critical infrastructure, operational technology environments often cannot be actively scanned, and yet active system feedback is needed for risk as

agentsarxiv-cs-ai

From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier

arXiv:2607.07779v1 Announce Type: cross Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in

GIRAF: Towards Generalizable Human Interactions with Articulated Objects

arXiv:2607.07880v1 Announce Type: new Abstract: Synthesizing realistic full-body human interactions with articulated objects is a fundamental challenge for embodied AI and graphics, with applications

HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales

model-releasesarxiv-cs-cv

arXiv:2607.08705v1 Announce Type: new Abstract: Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unp

Infinity-Parser2 Technical Report

arXiv:2607.07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl

MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction

arXiv:2607.08080v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) requires jointly identifying (aspect, opinion, sentiment) triples from a given review sentence. While large l

agentsarxiv-cs-cl

PhyMAGIC: Physical Motion-Aware Generative Inference with Confidence-guided LLM

arXiv:2505.16456v3 Announce Type: replace Abstract: Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. Howeve

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PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

arXiv:2607.08269v1 Announce Type: new Abstract: Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML. We prese

PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation

arXiv:2510.19475v2 Announce Type: replace Abstract: Monocular 3D human pose estimation remains a fundamentally ill-posed inverse problem due to the inherent depth ambiguity in 2D-to-3D lifting. While

Prismata: Confining Cross-Site Prompt Injection in Web Agents

arXiv:2607.08147v1 Announce Type: cross Abstract: Autonomous web agents promise to automate everyday browsing tasks, but inherit one of the web's oldest attack surfaces. Cross-Site Scripting proved th

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ProjAgent: Procedural Similarity Retrieval for Repository-Level Code Generation

arXiv:2607.08691v1 Announce Type: cross Abstract: Repository-level code generation requires implementing target functions while accounting for complex cross-file dependencies and project-specific conv

agentsarxiv-cs-ai

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

arXiv:2601.22588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as reference-free evaluators via prompting, but this 'LLM-as-a-Judge' paradigm is costly, opaque,

Retrieval of Scientific and Technological Resources for Experts and Scholars

arXiv:2204.06142v2 Announce Type: replace-cross Abstract: Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources

Search-based Testing of Vision Language Models for In-Car Scene Understanding

arXiv:2607.02300v2 Announce Type: replace Abstract: In the automotive domain, in-car scene understanding (ISU) enables the detection of safety-critical events, such as driver distraction, and supports

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Selective Left-Shift: Turning Test-Time Compute and Difficulty-based Curation into Training Data for Low-Resource Code Generation

arXiv:2607.07748v1 Announce Type: new Abstract: Large Language Models achieve strong code generation for high resource languages like Python and Java but suffer sharp performance drops on Low-Resource

researcharxiv-cs-lg

Applications

StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling

arXiv:2507.05240v2 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low

applicationsarxiv-cs-cv

Towards Isolated Interventions via Almost Orthogonal Features in Language Models

arXiv:2602.04718v2 Announce Type: replace-cross Abstract: A central premise in mechanistic interpretability is that meaningful concepts in language models are represented by linear features in activat

local-aiarxiv-cs-ai

TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories

arXiv:2607.08400v1 Announce Type: cross Abstract: LLM agents reach users through resellers, who may rebrand a developer's agent or substitute a cheaper model. When provenance is disputed, attribution

local-aiarxiv-cs-ai

TTHE: Test-Time Harness Evolution

arXiv:2607.08124v1 Announce Type: cross Abstract: The behavior of an LLM agent is determined not only by the underlying model, but also by its harness: the executable program that constructs context,

agentsarxiv-cs-lg

UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks

model-releasesarxiv-cs-cl

arXiv:2607.08768v1 Announce Type: new Abstract: The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operati