Search: “models”

Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds

arXiv:2607.28908v1 Announce Type: new Abstract: Reflection, the ability to revisit and revise prior reasoning, is central to how humans improve their answers. Large language models (LLMs) are increasi

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Research

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

DGX agent

arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rel

researcharxiv-cs-lg

3 Aug 2026

Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations

arXiv:2410.06665v4 Announce Type: replace-cross Abstract: This paper explores the characterization of equivariant linear layers for representations of permutations and related groups. Unlike tradition

SciFigPlag-Bench: A Benchmark for Provenance-Aware Scientific Figure Plagiarism Detection

arXiv:2607.29124v1 Announce Type: new Abstract: Scientific figures often encode the visual evidence behind scientific findings, yet figure plagiarism remains underexplored as a benchmarked multimodal

Sensitivity Analysis of GRU, LSTM and Transformer Encoder in Classification of Automated Driving Systems

arXiv:2607.28665v1 Announce Type: cross Abstract: Automated driving systems (ADSs) are becoming ubiquitous. Future Software Defined Vehicles (SDVs) may be able to run multiple ADSs, both native and af

safetyarxiv-cs-ai

Stem: Rethinking Causal Information Flow in Sparse Attention

arXiv:2603.06274v2 Announce Type: replace-cross Abstract: The quadratic computational complexity of self-attention remains a fundamental bottleneck for scaling Large Language Models (LLMs) to long con

researcharxiv-cs-ai

Hardware

Studying quantization trade-offs for efficient inference deployment in machine translation

arXiv:2607.29397v1 Announce Type: new Abstract: Deploying large language models in realistic server environments poses challenges, as the system needs to provide high-quality responses with low latenc

hardwarearxiv-cs-cl

TraceViT: Grounded Trace Supervision for Visual Abstract Reasoning

arXiv:2607.29586v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) tests whether a model can infer an unseen transformation from a few input-output examples and apply it to a

safetyarxiv-cs-ai

WitCert: Sound Runtime Risk Observability and Gating for KV-Cache Quantization

arXiv:2607.28699v1 Announce Type: cross Abstract: KV-cache quantization is validated today by offline benchmark averages; a deployed system cannot tell whether compression is damaging the request it i

AfriEconQA: A Benchmark for Quantitative and Temporal Reasoning over World Bank Economic Reports

arXiv:2601.15297v3 Announce Type: replace Abstract: Reliable question answering over long institutional documents requires more than topical retrieval: a system must localize the exact passage that su

AgentMap: Joint Equivalence and Subsumption Discovery for Ontology Matching

arXiv:2607.27130v1 Announce Type: new Abstract: Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The existing OM systems identify only

Auto Research for Materials: Auditable AI-Scientist Workflows with Held-Out Transfer

arXiv:2607.17100v2 Announce Type: replace-cross Abstract: Auto Research uses language-model agents to propose, implement, and evaluate machine-learning changes in a closed loop, but is usually judged

local-aiarxiv-cs-ai

Baikal: Structured Search for Deep Research over Data Lakes

arXiv:2607.27726v1 Announce Type: cross Abstract: Deep research over data lakes requires an LLM agent to investigate evidence across thousands of heterogeneous tables and passages to synthesize a repo

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

ClinLens: Towards Long-Horizon Coding Agents for Longitudinal Multimodal Clinical Data Science

arXiv:2607.26155v1 Announce Type: new Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical

Closed-Loop Bayesian Bandit Encoder with GRAND Receiver for a Bursty Interference Channel

arXiv:2607.15404v2 Announce Type: replace-cross Abstract: Interleaving mitigates burst errors but introduces decoding delay and removes temporal error structure that a channel-aware decoder could expl

researcharxiv-cs-lg

Continuous-time reinforcement learning for optimal switching over multiple regimes

arXiv:2512.04697v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time reinforcement learning (RL) for optimal switching problems across multiple regimes. We consider a type

DualAnchor: Preserving Language Priors and Improving Lexical Fidelity in Gloss-Free Sign Language Translation

arXiv:2607.27614v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led sign language translation (SLT), the task of converting sign-language videos into spoken-langua

safetyarxiv-cs-cl

Tutorials

Dynamically Scaled Activation Steering

arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat

tutorialsarxiv-cs-lg

EgoGVAE: Ego-body Mesh Reconstruction via Guided Variational Autoencoder

arXiv:2607.27755v1 Announce Type: new Abstract: We address the problem of recovering the full-body mesh from only the head pose. This task has become essential for various applications based on head-m

EmoFeedback^2: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

arXiv:2511.19982v3 Announce Type: replace Abstract: Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions

safetyarxiv-cs-cv

EvoCause: LLM-Guided Evolution of Causal Graphs for Root Cause Analysis

arXiv:2607.27290v1 Announce Type: new Abstract: Modern telecommunication, cloud, and microservice systems emit correlated alarm cascades when components fail. Root cause analysis (RCA) aims to identif

FeatFix: Reuse What You Verify through Local Exact-Feature Correction for Faster Cached Diffusion Inference

arXiv:2607.27842v1 Announce Type: new Abstract: Diffusion models are widely used to generate high-quality images and videos, but their iterative denoising process remains computationally intensive. A

local-aiarxiv-cs-cv

FinanceHarness: Autonomous Financial Deep Research Framework

arXiv:2607.27853v1 Announce Type: new Abstract: Powered by advances in LLMs and autonomous agents, deep research has become one of the most widely adopted agentic products. However, most deep research

First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on f

local-aiarxiv-cs-lg

FlexiGrad: Adaptive Gradient Modulation for Hierarchical Fine-Grained Classification

arXiv:2607.17563v2 Announce Type: replace Abstract: Many fine-grained recognition tasks contain hierarchical labels such as order, family and species. Although this supervision should be beneficial, j

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize

arXiv:2607.27389v1 Announce Type: new Abstract: Learning-to-optimize (L2O) methods accelerate repeated optimization by training models to predict solutions, warm starts, branching decisions, or other

researcharxiv-cs-lg

GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation

arXiv:2602.14649v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit strong reasoning abilities, but their high computational costs limit their practical deployment. Recent studies

researcharxiv-cs-cl

Group-Reflective Self-Distillation for Agentic Reinforcement Learning

arXiv:2607.28076v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is effective for training large language model agents. However, terminal rewards provide only co

safetyarxiv-cs-lg

GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoning

arXiv:2607.26160v1 Announce Type: new Abstract: Clinical practice guidelines (CPGs) encode diagnostic criteria, but LLM systems typically retrieve guideline text or absorb it through training rather t

GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference

arXiv:2607.27694v1 Announce Type: cross Abstract: Low-bit quantization is essential for efficient LLM inference, and both rotation and fine-grained group quantization have shown individual promise. Ho

Applications

HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data

arXiv:2607.27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated wit

applicationsarxiv-cs-lg

ID-Guard: A Universal Framework for Combating Facial Manipulation via Breaking Identification

arXiv:2409.13349v3 Announce Type: replace Abstract: The misuse of deep learning-based facial manipulation poses a serious threat to civil rights. To prevent such fraud at its source, proactive defense

researcharxiv-cs-cv

IDP AutoOpt: Agent-Driven Optimization of Document Processing Pipeline Configurations

arXiv:2607.26075v1 Announce Type: cross Abstract: We present IDP AutoOpt, an autonomous LLM agent that discovers high-performing configurations for intelligent document processing (IDP) pipelines. Tun

Improving Mental Health Screening and Early Risk Detection in Spanish

arXiv:2607.28476v1 Announce Type: new Abstract: Early detection of mental health disorders is often limited by the lack of specialized resources in Spanish and the difficulty of analyzing long histori

researcharxiv-cs-cl

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification

arXiv:2607.28428v1 Announce Type: cross Abstract: We introduce Kohn--Sham Spectral Embedding (KSSE), a physics-inspired energy-based model replacing dense CNN classifiers with a sparse-graph spectral

local-aiarxiv-cs-cv

LayerRAG-Bench: A Cross-Layer Reliability Benchmark for Agentic Retrieval-Augmented Generation

arXiv:2607.27353v1 Announce Type: new Abstract: Agentic retrieval-augmented generation systems can produce answers that appear grounded while failing at the evidence, tool-contract, authorization, or

Learning-Augmented and Randomized Algorithms for Line Aggregation with Delays

arXiv:2607.27807v1 Announce Type: new Abstract: This paper studies learning-augmented and randomized online aggregation with delays on a line metric. We consider advice given as online suggested servi

Learning features from Newton's algorithm: a way to accelerate nonlinear parametrized PDE solvers

arXiv:2607.28036v1 Announce Type: new Abstract: It is well known that Newton's method converges faster when the initial guess is closer to a root of a system of nonlinear equations. In this paper, a t

Learning to Trace Seiberg Dualities

arXiv:2607.28628v1 Announce Type: cross Abstract: Dualities play an important role in establishing both microscopic and emergent phenomena in a wide range of physical systems. In practice, though, it

LLM-Guided Initialization for Accelerated Hybrid Quantum-Classical Medical Image Classification

arXiv:2607.27262v1 Announce Type: cross Abstract: Variational quantum algorithms often encounter barren plateaus, where cost gradients decay rapidly with increasing circuit depth, undermining the trai

Looped Transformers with Source-Centered State Evolution

arXiv:2607.27656v1 Announce Type: cross Abstract: Looped Transformers create a useful train- and test-time compute axis by reusing the same Transformer block over recurrent depth, increasing effective

Agents

MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memory

arXiv:2607.27834v1 Announce Type: cross Abstract: Persistent memory lets long-running large language model agents reuse information across sessions and tasks. Yet errors in writable memory can persist

agentsarxiv-cs-cl

MUGEN: A Unified Framework for Efficient Motion Understanding and Generation

arXiv:2607.27581v1 Announce Type: new Abstract: Grounding human motion in language, and language in motion, is a central step toward physical AI systems that can understand, generate, and communicate

safetyarxiv-cs-lg

MUL-T: Decoding Spatial Cellular Architecture in Multiplexed Tissue Images

arXiv:2607.28030v1 Announce Type: cross Abstract: Understanding tissue organisation in multiplexed imaging requires modelling both cellular phenotypes and their spatial context. Existing approaches ty

researcharxiv-cs-cv

Agents

Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges

arXiv:2607.26212v1 Announce Type: cross Abstract: Multi-Agent Debate (MAD) is a promising paradigm for improving the accuracy and robustness of Large Language Model (LLM)-based agentic systems. It ena

agentsarxiv-cs-ai

Objective-Aligned Direct Answer SFT for Robust Multi-Frame Medical VQA

arXiv:2607.27566v1 Announce Type: new Abstract: Multi-frame medical VQA appears to reward increasingly complex adaptation: controller-style inference, localization-aware reranking, static hard-negativ

One Patch Is Enough: Reinforcement-Optimized Visual Token Grounding for MLLM-Based Scene Text Spotting

arXiv:2607.27902v1 Announce Type: new Abstract: Scene text spotting requires high-precision alignment between textual recognition and spatial localization. While visual-token grounding has emerged as