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Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics

arXiv:2606.31134v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evad

agentsarxiv-cs-ai

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BlockPilot: Instance-Adaptive Policy Learning for Diffusion-based Speculative Decoding

DGX agent

arXiv:2606.31315v1 Announce Type: new Abstract: Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in parallel, and are then verified by the tar

safetyarxiv-cs-cl

1 Jul 2026

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams

arXiv:2606.22723v2 Announce Type: replace Abstract: Although Large Language Models (LLMs) excel in many tasks, their assessment in Portuguese has received less attention, particularly for open-ended,

BP-TTA: Balanced and Prototype-Guided Test-Time Adaptation in Dynamic Scenarios

arXiv:2606.31420v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enables models trained on a source domain to adapt online to unlabeled test data under distribution shifts. While recent TTA

safetyarxiv-cs-ai

Breaking Failure Cascades: Step-Aware Reinforcement Learning for Medical Multimodal Reasoning

arXiv:2606.31825v1 Announce Type: cross Abstract: Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantl

safetyarxiv-cs-ai

Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration

arXiv:2601.19506v4 Announce Type: replace Abstract: Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrai

safetyarxiv-cs-cv

Local Ai

Bridging Local Observation and Global Simulation in Closed-Loop Traffic Modeling

arXiv:2606.31844v1 Announce Type: cross Abstract: A local-to-global context mismatch arises when autoregressive traffic simulators trained on ego-centric driving logs are deployed in globally observab

local-aiarxiv-cs-ai

Bridging Scientific Heritage: An Arabic--Russian Parallel Corpus and LLM Benchmark for Sustainable Knowledge Transfer

arXiv:2606.30943v1 Announce Type: new Abstract: Russian and Arabic are among the major languages of scientific communication. Language barriers impede the exchange of research results between these co

Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers

arXiv:2606.31779v1 Announce Type: cross Abstract: Language models typically reason via explicit chain-of-thought (CoT), generating intermediate steps token-by-token. Latent CoT offers an alternative:

researcharxiv-cs-cl

Bridging Video Understanding and Generation in a Unified Framework

arXiv:2606.31326v1 Announce Type: new Abstract: Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video dom

researcharxiv-cs-cv

Budget-Adaptive Routing: Skipping the Weak When the Strong Answers Anyway

arXiv:2606.30919v1 Announce Type: cross Abstract: Edge-cloud inference collaborations are often designed with a routing estimator that decides whether to offload each frame from weak models at the edg

researcharxiv-cs-ai

Building a Multimodal Dataset of Academic Paper for Keyword Extraction

arXiv:2606.31069v1 Announce Type: new Abstract: Up to this point, keyword extraction task typically relies solely on textual data. Neglecting visual details and audio features from image and audio mod

tutorialsarxiv-cs-cl

Building an ASR Solution for Training and Assessing Children's Reading

arXiv:2606.31508v1 Announce Type: new Abstract: Automatic speech recognition for children's reading remains underdeveloped for most African languages, including Bambara, despite its potential value fo

Calibrating the Evaluator: Does Probability Calibration Mitigate Preference Coupling in LLM Agent Feedback Loops?

arXiv:2606.31371v1 Announce Type: cross Abstract: When large language model (LLM) agents adapt their behavior through evaluator feedback, systematic evaluator biases propagate into the agent's learned

Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models

model-releasesarxiv-cs-lg

arXiv:2606.31630v1 Announce Type: new Abstract: Language models increasingly write probabilistic programs (in NumPyro, Stan, or Pyro), but a program that compiles, runs, and passes every unit test can

Can LLMs Imagine Moral Alternatives Beyond Binary Dilemmas?

arXiv:2606.31213v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed as moral advisors and agents, they need to address dilemmas between two competing values. Ho

agentsarxiv-cs-ai

Can Physician Expertise Improve Machine Learning Identification of Delirium?

arXiv:2606.30651v1 Announce Type: cross Abstract: Delirium is common in hospitalized patients and is often missed in routine care. We present a user-centered interactive machine learning (UC-iML) fram

Can Tabular In-Context Learners Generalize to Biomolecular Property Prediction?

arXiv:2606.31126v1 Announce Type: new Abstract: Predicting biomolecular properties from limited labeled data is a central bottleneck in protein engineering and small-molecule design. As strong pretrai

safetyarxiv-cs-lg

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation

arXiv:2603.23867v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have been applied to a wide range of reasoning tasks, yet it remains unclear whether they can reason robustly un

researcharxiv-cs-ai

Applications

Capturing Context-Aware Route Choice Semantics for Trajectory Representation Learning

arXiv:2510.14819v3 Announce Type: replace Abstract: Trajectory representation learning (TRL) aims to encode raw trajectory data into low-dimensional embeddings for downstream tasks such as travel time

applicationsarxiv-cs-cv

CasaMaestro: Multi-View Panoramas for House-Scale 3D Reconstruction

arXiv:2606.31086v1 Announce Type: new Abstract: The rise of home-deployed embodied AI systems is driving a growing need for fast, metric 3D reconstruction of residential spaces to support navigation,

safetyarxiv-cs-cv

CDR-Bench: Evaluating Faithful Execution of Compositional, Order-Sensitive Data Refinement Recipes

arXiv:2606.31435v1 Announce Type: new Abstract: Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators dete

Certified Speculative Execution for Untrusted AI Agents

arXiv:2606.31023v1 Announce Type: cross Abstract: Hard-constrained sequential decision systems have no certified way to spend the test-time compute of modern AI: executing the multi-step drafts of a l

safetyarxiv-cs-lg

CharDiff-LP: A Diffusion Model with Character-Level Guidance for License Plate Image Restoration

arXiv:2510.17330v3 Announce Type: replace-cross Abstract: License plate image restoration is important not only as a preprocessing step for license plate recognition but also for enhancing evidential

researcharxiv-cs-ai

CHERRY: Compressed Hierarchical Experts with Recurrent Representational Yield

arXiv:2606.31796v1 Announce Type: cross Abstract: We study three complementary techniques for training compute-efficient language models. (1) Selective supervision and per-token efficiency. Selective

ChronoFlow-Policy: Unifying Past-Current-Future Interaction Flow in Visuomotor Policy Learning

arXiv:2606.31493v1 Announce Type: new Abstract: Visual signals play a crucial role in policy learning by enabling models to capture object motion and interaction dynamics. Just as humans reason about

safetyarxiv-cs-ro

Citation Discipline in Spec-Driven Development: A Cross-Model Empirical Study of Output Determinism and Automated Hallucination Detection in LLM-Generated Code

arXiv:2606.30689v1 Announce Type: cross Abstract: Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ funda

ClawArena-Team: Benchmarking Subagent Orchestration and Dynamic Workflows in Language-Model Agents

arXiv:2606.31174v1 Announce Type: new Abstract: Production large language-model (LLM) agents are increasingly deployed not as lone problem-solvers but as managers: a main model creates specialized sub

CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning

arXiv:2606.31608v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong results on many medical benchmarks, but their clinical reasoning remains difficult to evaluate reliably. A c

safetyarxiv-cs-cl

CLIMB: Centroid-Based Hierarchical Memory for Online Continual Self-Supervised Learning

arXiv:2606.31275v1 Announce Type: cross Abstract: Online Continual Self-Supervised Learning (OCSSL) aims to learn representations from a continuous stream of unlabeled data, without knowledge of task

tutorialsarxiv-cs-ai

Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering

arXiv:2606.31432v1 Announce Type: new Abstract: Medical multiple-choice question answering requires parameter-efficient adaptation across heterogeneous knowledge domains and reasoning operations. A me

CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac

safetyarxiv-cs-ai

Coarsening Bias from Variable Discretization in Causal Functionals

model-releasesarxiv-cs-lg

arXiv:2602.22083v2 Announce Type: replace-cross Abstract: Causal identification functionals often require integration over conditional densities of continuous variables, such as those arising in nonpa

CoDex: Learning Compositional Dexterous Functional Manipulation without Demonstrations

arXiv:2606.31909v1 Announce Type: new Abstract: In this work, we study Compositional Dexterous Functional Object Manipulation (CD-FOM): tasks such as aiming and actuating a spray bottle on a plant or

tutorialsarxiv-cs-ro

Collaborative Knowledge Distillation via a Learning-by-Education Node Community

arXiv:2410.00074v2 Announce Type: replace Abstract: A novel Learning-by-Education Node Community framework (LENC) for Collaborative Knowledge Distillation (CKD) is presented, which facilitates continu

agentsarxiv-cs-lg

CoLT: Teaching Multi-Modal Models to Think with Chain of Latent Thoughts

model-releasesarxiv-cs-cv

arXiv:2606.31986v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has enabled multi-modal large language models (MLLMs) to tackle complex visual reasoning tasks by generating explicit i

ComAct: Reframing Professional Software Manipulation via COM-as-Action Paradigm

arXiv:2606.13239v2 Announce Type: replace-cross Abstract: Existing computer-use agents remain fundamentally limited in professional software manipulation: GUI-based agents suffer from fragile visual g

Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation

arXiv:2602.08557v2 Announce Type: replace Abstract: Training non-prehensile manipulation policies in contact-rich settings is a core challenge in robotics. While Reinforcement Learning (RL) has demons

researcharxiv-cs-ro

CoMet: Context and Multiplicity Decomposition for Multimodal Uncertainty Estimation

arXiv:2606.32012v1 Announce Type: cross Abstract: Uncertainty estimation has been a long-standing challenge in AI models; it amounts to 'knowing what you don't know,' and metacognition is notoriously

researcharxiv-cs-cv

Communication-Aware Robot Execution for Cloud Inference under Spatially Heterogeneous Connectivity

arXiv:2606.31497v1 Announce Type: new Abstract: Cloud-hosted foundation models enable robots to use semantic reasoning beyond onboard computational limits. In this setting, the robot executes a curren

researcharxiv-cs-ro

CoMNet: A MedNeXt-CorrDiff Framework for Multi-Site Brain Tumor Segmentation

arXiv:2606.15305v2 Announce Type: replace Abstract: Accurate brain tumor segmentation from multiparametric magnetic resonance imaging (MRI) is critical for treatment planning, response assessment, and

tutorialsarxiv-cs-cv

Applications

Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks

arXiv:2606.31594v1 Announce Type: cross Abstract: The Internet of Things (IoT) is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more. Despite

applicationsarxiv-cs-ai

Local Ai

ComplianceGate: Classifier-Gated Multi-Tier LLM Routing for Inference in Regulated Industries

arXiv:2606.31163v1 Announce Type: cross Abstract: Large language models deployed in regulated industries operate under two constraints: compliance enforcement and cost efficiency. Personally identifia

local-aiarxiv-cs-ai

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning

arXiv:2502.00684v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has successfully addressed many complex control problems. However, the neural networks representing policies

agentsarxiv-cs-ai

Conditional Tropical Cyclogenesis Rates via Rare-Event Sampling in a Neural Weather Emulator

arXiv:2606.30920v1 Announce Type: cross Abstract: We couple Forward Flux Sampling (FFS), a non-equilibrium rare-event technique from statistical mechanics, to a neural weather emulator (SDL-WXFormer,

researcharxiv-cs-lg

Conformalized Regression for Continuous Bounded Outcomes

arXiv:2507.14023v2 Announce Type: replace-cross Abstract: Regression problems with bounded continuous outcomes frequently arise in statistical and machine learning applications, such as the analysis o

researcharxiv-cs-lg

Constrained Online Convex Optimization without Slater's Condition

arXiv:2606.31480v1 Announce Type: new Abstract: We study constrained online convex optimization with adversarial losses and stochastic or adversarial constraints. For stochastic constraints, existing

researcharxiv-cs-lg

Contextual Slate GLM Bandits with Limited Adaptivity

model-releasesarxiv-cs-lg

arXiv:2606.31449v1 Announce Type: new Abstract: We investigate the contextual slate bandit problem with generalized linear rewards under limited adaptivity. At each round, the learner is presented wit