Search: “models”

Adaptive Margin RLHF via Preference over Preferences

arXiv:2509.22851v4 Announce Type: replace-cross Abstract: Margin-based optimization is fundamental to improving generalization and robustness in classification tasks. In the context of reward model le

safetyarxiv-cs-ai

Applications

Advances in Neural Controlled Differential Equations

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DGX agent

arXiv:2607.05280v1 Announce Type: new Abstract: Many real-world systems evolve continuously, yet most machine learning models interpret time series as discrete sequences. Continuous-time approaches in

applicationsarxiv-cs-lg

7 Jul 2026

Agent Step Value: State-Transition Measurement with State-Grounded LLM Evaluators

arXiv:2607.04419v1 Announce Type: new Abstract: Most agent evaluations collapse a multi-step trace into a final answer, a success flag, or a trajectory-level score. These aggregates obscure the diagno

Agentic Retrieval-Augmented Generation for Financial Document Question Answering

arXiv:2605.05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual na

AgenticPD: A Stage-Aware Agentic Framework for Physical Design QoR Optimization

arXiv:2607.04758v1 Announce Type: new Abstract: Physical design quality-of-results~(QoR) optimization is hard and expensive. Choices made at one stage can help or hurt later stages. Each evaluation re

Air-Plan: Query-Optimized Topology Selection for Over-the-Air Decentralized Federated Learning

arXiv:2607.04254v1 Announce Type: cross Abstract: Over-the-air (OTA) aggregation exploits the superposition property of wireless multiple-access channels to aggregate model updates from multiple devic

researcharxiv-cs-lg

AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario

arXiv:2506.16898v2 Announce Type: replace Abstract: Diffusion-based text-to-image models are increasingly used for urban analysis and scenario generation, but their geographic knowledge and representa

An AI-Assisted Solution to the Signed BAR Conjecture: Uniqueness in the Harrison--Reiman Class and a Completely-S Class Obstruction

arXiv:2607.03639v1 Announce Type: cross Abstract: For a multidimensional reflected diffusion, determining whether the associated basic adjoint relationship (BAR) uniquely characterizes the stationary

Analytical Standard Errors for Exploratory Factor Solutions

arXiv:1811.05336v2 Announce Type: replace-cross Abstract: Inference for factor models is often hampered by the lack of tractable and accurate variance estimates, which can materially distort downstrea

researcharxiv-cs-lg

APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries

arXiv:2510.24380v2 Announce Type: replace Abstract: Make-on-demand combinatorial synthesis libraries (CSLs) like Enamine REAL have significantly enabled drug discovery efforts. However, their large si

Attention is Just Another Name for Coupling? A Fast-Slow ODE Perspective on Hierarchical Pretraining

arXiv:2606.16730v2 Announce Type: replace-cross Abstract: We re-interpret Transformer pretraining as a fast-slow, singularly perturbed flow along depth, with untied weights as its non-autonomous featu

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems

arXiv:2607.04433v1 Announce Type: cross Abstract: The rapid integration of large language model-based agents into recommender systems has driven a shift from static, ranking-based pipelines toward aut

safetyarxiv-cs-cl

AutoResearch: An Execution-Grounded Multi-Agent Framework for Reliable Research Workflow Automation

arXiv:2607.02520v1 Announce Type: cross Abstract: Automated research agents increasingly generate code, retrieve literature, and draft scientific artifacts, but they often fail to verify whether gener

BanglaMemeEvidence: A Multimodal Benchmark Dataset for Explanatory Evidence Detection in Bengali Memes

arXiv:2607.03981v1 Announce Type: cross Abstract: Memes have become influential communication tools on social media, combining viral visuals with concise messaging to convey impactful ideas. While sub

Be Indiscrete: The Benefits of Learning Continuous Spine Degeneration Severity Scores

arXiv:2607.05090v1 Announce Type: new Abstract: Lumbar spine degeneration is a major contributor to chronic low back pain and is routinely assessed on MRI using ordinal grading systems, e.g. normal, m

researcharxiv-cs-cv

Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents

arXiv:2604.00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and

Boundary-layer asymptotics for Gaussian-smoothed singular measures

arXiv:2607.04514v1 Announce Type: cross Abstract: We study the small-noise asymptotics of Euclidean heat regularizations of probability measures supported on manifolds with corners. Near a boundary or

Breaking the One-Dimensional Expressibility-Trainability Tradeoff

arXiv:2607.04598v1 Announce Type: cross Abstract: Expressive parameterized quantum circuits (PQCs) are often designed under a dilemma: the growth of expressibility and entangling power (EP) that impro

Bridging Interleaved Multi-Modal Reasoning as a Unified Decision Process

arXiv:2607.03748v1 Announce Type: new Abstract: Unified multi-modal models (UMMs) have shown promising interleaved text-image reasoning capabilities, yet effectively optimizing such multi-turn generat

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Can Conversational Temporal Dynamics Improve Depression Detection in Dyads? A Preliminary Investigation in Multi-Modality Perspectives

arXiv:2607.03744v1 Announce Type: new Abstract: Automatic depression detection from clinical interviews typically models the semantic content and acoustic characteristics of participant speech. Howeve

Tutorials

Canonical quantization of neurons

arXiv:2607.05000v1 Announce Type: cross Abstract: Canonical quantization provides a systematic procedure for constructing quantum models from classical Hamiltonians. Here, we apply this principle to a

tutorialsarxiv-cs-lg

CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes

arXiv:2404.01299v3 Announce Type: replace-cross Abstract: Causal video question answering (QA) has garnered increasing interest, yet existing datasets often lack depth in causal reasoning. To address

Chronos: The AI Co-Historian

arXiv:2604.03553v2 Announce Type: replace Abstract: AI is increasingly supporting, accelerating, and automating scientific discovery across subjects. Yet, the adoption of AI in historical research rem

CLABTOOLKIT: An Open-Source Toolkit for Routine Processing, Manipulation, and Visualization of Neuroimaging Data

arXiv:2607.02638v1 Announce Type: new Abstract: Neuroimaging research requires manipulating heterogeneous data structures, including raw MRI volumes, volumetric parcellations, cortical surface meshes,

ClassicLogic: A Knowledge-Driven Benchmark of Classic Puzzle Games for Evaluating Compositional Generalization

arXiv:2607.05185v1 Announce Type: new Abstract: Compositional generalization, the ability to understand and produce novel combinations of known components, remains a fundamental challenge for modern a

ComplexMimic: Human-Scene Interaction Imitation in Complex 3D Environments

arXiv:2607.02034v2 Announce Type: replace Abstract: Physics-based Human-Scene Interaction (HSI) imitation learning is crucial for embodied intelligence as it bridges the gap between kinematic 3D motio

Applications

CompLLM: Compression for Long Context Q&A

arXiv:2509.19228v2 Announce Type: replace Abstract: Large Language Models (LLMs) face significant computational challenges when processing long contexts due to the quadratic complexity of self-attenti

applicationsarxiv-cs-cl

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language

arXiv:2607.03882v1 Announce Type: cross Abstract: LLMs are increasingly deployed as post-hoc explainers of AI-generated outputs, yet it remains unclear whether they can reliably communicate probabilis

Context Tuning for In-Context Optimization

arXiv:2507.04221v3 Announce Type: replace-cross Abstract: We introduce Context Tuning, a simple and effective method to significantly enhance few-shot adaptation of large language models (LLMs) withou

CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation

arXiv:2607.02576v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts pretrained weights through low-rank updates, and recent methods further exploit the singular va

CSB: A Counting and Sampling tool for Bit-vectors

arXiv:2607.04142v1 Announce Type: cross Abstract: Satisfiability modulo theory (SMT) solvers have significantly advanced automated reasoning due to their effectiveness in solving problems across vario

Local Ai

Ctrl-Z Sampling: Scaling Diffusion Sampling with Controlled Random Zigzag Explorations

arXiv:2506.20294v5 Announce Type: replace Abstract: Diffusion models generate conditional samples by progressively denoising Gaussian noise, yet the denoising trajectory can stall at visually plausibl

local-aiarxiv-cs-cv

Local Ai

Curated retrieval versus open web search in public AI information services: a coverage-trust trade-off

arXiv:2607.05217v1 Announce Type: cross Abstract: Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web

local-aiarxiv-cs-cl

Local Ai

Decentralised Federated Learning over Temporal Networks: The Role of Heterogeneities

arXiv:2607.03171v1 Announce Type: cross Abstract: Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, pro

local-aiarxiv-cs-ai

Decentralized Aggregation of LLM Predictions via Wagering Mechanisms

arXiv:2607.04389v1 Announce Type: new Abstract: It is increasingly common to aggregate predictions from multiple LLMs, each with domain expertise or access to private tools and data, to improve collec

safetyarxiv-cs-ai

Deep Generative Spatiotemporal Engression for Probabilistic Forecasting of Epidemics

arXiv:2603.07108v2 Announce Type: replace-cross Abstract: Accurate and reliable forecasting of epidemic incidences is critical for public health preparedness, yet it remains a challenging task due to

researcharxiv-cs-lg

Distill Where the Student Goes: Teacher-Regularized RL for English-Evidence Cross-Lingual RAG

arXiv:2607.02966v1 Announce Type: new Abstract: Cross-lingual retrieval-augmented generation (RAG) is often deployed in an English-evidence regime, where users query in diverse languages but retrieved

safetyarxiv-cs-cl

Don't Wait to Reply: Towards Responsive yet Thoughtful Dialogue through Proactive Thinking

arXiv:2607.03093v1 Announce Type: cross Abstract: Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks. However, its reactive nature, where reasoning i

DualView: Preventing Indirect Prompt Injection in Personal AI Agents

arXiv:2607.03821v1 Announce Type: cross Abstract: Personal AI agents that run on the user's local machine, such as OpenClaw, automate daily tasks including web search, email, and file management. Thei

Echoes of Unrest: A Multimodal NLP Framework for Early Warning of Fake News and Violence-Driven Mob Activity

arXiv:2607.02734v1 Announce Type: cross Abstract: Rapid growth in social media has transformed global communication by enabling fast information exchange, but it has also accelerated the spread of mis

ECO: Incremental Ego-Centric Octree Update for Point Streams

model-releasesarxiv-cs-ro

arXiv:2607.05092v1 Announce Type: new Abstract: Constructing octrees for mobile robots that process continuous point streams in real time poses significant computational and memory challenges. Standar

Agents

EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments

arXiv:2607.05155v1 Announce Type: new Abstract: Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deploy

agentsarxiv-cs-cl

Agents

EEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection

arXiv:2607.04558v1 Announce Type: cross Abstract: Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing de

agentsarxiv-cs-ai

EgoInertia-MI: A Multimodal Egocentric Vision and IMU Benchmark for Motor Impairment Assessment

arXiv:2607.03934v1 Announce Type: new Abstract: Motor impairments, including tremor, bradykinesia, gait abnormalities, and postural instability, are common across many neurological and movement-relate

Evaluating LLM Uncertainty in Long-Form Generation Using Deterministic Ground Truth

arXiv:2607.03870v1 Announce Type: new Abstract: As LLMs generate increasingly long outputs, effective uncertainty estimation must identify errors at fine-grained levels rather than discard entire resp

FairFlow: Demystifying and Mitigating Stereotype Bias in Text-to-Image Diffusion Transformers

arXiv:2607.03180v1 Announce Type: new Abstract: Multimodal diffusion transformers (MM-DiTs) have emerged as the prevalent backbone for modern text-to-image generation systems. However, they exhibit cr

Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures

arXiv:2404.06294v2 Announce Type: replace-cross Abstract: Super-Resolution (SR) is a time-hallowed image processing problem that aims to improve the quality of a Low-Resolution (LR) sample up to the s

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline

arXiv:2607.04448v1 Announce Type: cross Abstract: Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) po