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Don't Repeat Yourself: Stopping Verbatim Loops at Sampling Time

arXiv:2608.22761v1 Announce Type: cross Abstract: Large Language Models generate text autoregressively, but open-ended generation is prone to verbatim looping, in which models repeat spans already pre

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DRAgent: Discriminative Reasoning Agent for Referring Expression Segmentation

DGX agent

arXiv:2608.22885v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) aims to generate a pixel-level mask for the object specified by a language expression. Recent methods based on m

local-aiarxiv-cs-cv

25 Aug 2026

DRBD-Mamba for Robust and Efficient Brain Tumor Segmentation with Analytical Insights

arXiv:2510.14383v4 Announce Type: replace Abstract: Accurate brain tumor segmentation is significant for clinical diagnosis and treatment but remains challenging due to tumor heterogeneity. Mamba-base

local-aiarxiv-cs-cv

DreamMimic: Learning Visuomotor Whole-Body Loco-Manipulation via World Model

arXiv:2608.22278v1 Announce Type: new Abstract: Vision-based whole-body loco-manipulation on humanoid robots is challenging due to partial observability, contact-rich dynamics, and the difficulty of l

safetyarxiv-cs-ro

Dual-Grained Agent Memory and Shapley Context Attribution for Multimodal Agentic Learner

model-releasesarxiv-cs-cv

arXiv:2608.23268v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-lev

Dual-Layer Agentic Memory with Fast Write Routing and Slow Consolidation

model-releasesarxiv-cs-cl

arXiv:2608.22215v1 Announce Type: new Abstract: Large language model (LLM) agents operate in dynamic environments where knowledge continuously evolves. Existing memory systems typically treat external

Dual-Scale State-Space Modeling with Speaker-Wise Dynamic CRF for Speech Emotion Recognition in Conversation

arXiv:2608.22399v1 Announce Type: new Abstract: Conversational speech emotion recognition must reconcile acoustic evidence across temporal scales with two interaction processes: cross-speaker contextu

local-aiarxiv-cs-lg

DuoGNN: Topology-aware Graph Neural Network with Homophily and Heterophily Interaction-Decoupling

model-releasesarxiv-cs-lg

arXiv:2409.19616v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have proven effective in various medical imaging applications, such as automated disease diagnosis. However, due to the

DynaContext: Self-Improving Dynamic Contextualization of Optimized Prompts for Heterogeneous Parameter Extraction

arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza

Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair

arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix gen

agentsarxiv-cs-ai

Dynamic Topic Modeling for Cross-Corpus Temporal Analysis

arXiv:2608.23284v1 Announce Type: new Abstract: Dynamic Embedded Topic Models (D-ETM) provide an interpretable framework for modeling temporal semantic evolution, but cross-corpus comparison remains d

safetyarxiv-cs-cl

DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning

arXiv:2603.16459v2 Announce Type: replace Abstract: Diffusion large language models (D-LLMs) have emerged as a promising alternative to auto-regressive models due to their iterative refinement capabil

researcharxiv-cs-cl

DySCo: Dynamically consistent data-driven downscaling of extremes in climate projections

arXiv:2608.21998v1 Announce Type: new Abstract: Regional climate risk assessment is critical for applications such as infrastructure design, disaster forecasting, and insurance resource allocation. Ho

researcharxiv-cs-lg

E2S-Pruner: Progressive Two-Stage Evidence Fusion for Visual Token Pruning in Vision-Language Models

arXiv:2608.23253v1 Announce Type: cross Abstract: Vision-language models typically encode an image into hundreds of visual tokens, incurring substantial inference latency and GPU memory overhead. Exis

local-aiarxiv-cs-ai

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

arXiv:2608.23525v1 Announce Type: new Abstract: Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards mak

ECHO: A Cognitively Inspired, Auditable Memory Plane for Long-Horizon Agents

arXiv:2608.21755v1 Announce Type: new Abstract: Long-horizon agents need memory that identifies relevant experience, resolves revisions, and exposes checkable provenance. We present ECHO (Embodied Con

EchoWM: Open and Enterable Omnimodal World Models

arXiv:2608.23189v1 Announce Type: new Abstract: We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, e

tutorialsarxiv-cs-cv

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

arXiv:2608.21946v1 Announce Type: cross Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable expl

safetyarxiv-cs-ai

EditStream: A Unified Autoregressive Framework for Interactive Video Generation and Editing

arXiv:2608.21424v1 Announce Type: new Abstract: Interactive video generation and editing are becoming increasingly important for creative design. In this report, we introduce EditStream: a unified fra

researcharxiv-cs-cv

Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games

arXiv:2505.24255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for com

Efficient Regression Models for Scan Statistics

arXiv:2608.22201v1 Announce Type: cross Abstract: We introduce a new class of regression models for scan statistics on real-valued signals. These allow for improved fitting of non-stationary signals t

researcharxiv-cs-lg

EG-ARSA: An Expert-Grounded Open Model for Visual Road Safety Auditing in Low-Resource Settings

arXiv:2608.23563v1 Announce Type: cross Abstract: Road traffic injuries remain a major challenge in low- and middle-income countries, where proactive road safety auditing is limited by incomplete cras

EGAMA-RC: Risk-Calibrated Evidence-Gated Adaptive Malware Analysis for Robust and Interpretable Memory-Forensic Triage

arXiv:2608.22721v1 Announce Type: cross Abstract: Machine-learning malware detectors often achieve high clean-data accuracy, but operational triage also requires evidence about uncertainty, novelty, r

researcharxiv-cs-lg

Emotion Intensity Matters: Generating Realistic Expressions in Virtual Humans with CVAEs

arXiv:2608.21697v1 Announce Type: new Abstract: Generating expressive facial behavior in virtual humans (VHs) remains a central challenge in affective computing and character animation. This paper pre

researcharxiv-cs-cv

EMPIRE: Explicit Manipulation Planning as a Learnable Intermediate Representation for Egocentric Hand-Motion Forecasting

arXiv:2608.22449v1 Announce Type: cross Abstract: Forecasting dexterous hand motions from egocentric observations is fundamental to intelligent interactive systems. Existing VLM-based methods typicall

tutorialsarxiv-cs-ai

ENCORE: Entropy-Guided Cropping and Attention Regularization for Robust Vision--Language Understanding

model-releasesarxiv-cs-cv

arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution su

EndoNav: Semantic-to-Geometric Grounding for Language-Guided Robotic Endoscopic Examination

arXiv:2608.22093v1 Announce Type: new Abstract: Minimally invasive procedures performed within confined anatomical spaces depend on continuous endoscopic visualization. Current robotic endoscope syste

agentsarxiv-cs-ro

Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting

arXiv:2608.21463v1 Announce Type: new Abstract: The study employed an Artificial Neural Network in combination with the optimized Adaptive Moment Estimation (Adam) algorithm, currently the only AQI fo

Enhancing Sim2Real Transfer for Torque-Controlled Robots through Real2Sim Dynamics Estimation and Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2608.22629v1 Announce Type: new Abstract: Transferring reinforcement learning policies from simulation to Real-World robots remains a major challenge, particularly when dealing with low-level to

Enrich-Retrieve-Rank: Scaling Capability Discovery Beyond In-Context Routing

arXiv:2608.22695v1 Announce Type: cross Abstract: Agent ecosystems now include thousands of MATS components (Models, Agents, Tools, and Skills), yet their discovery still relies on in-context routing.

agentsarxiv-cs-ai

Entity-Constrained CBCT Retrieval for Low-Resource Dental Record Completion

model-releasesarxiv-cs-cv

arXiv:2608.21913v1 Announce Type: new Abstract: Completing dental records from cone-beam computed tomography (CBCT) is difficult when annotation is scarce and individual clinical fields are supported

Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads

arXiv:2508.02609v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNN) have been extensively applied to industry recommendation systems, as seen in models like GraphSageite{GraphSage},

tutorialsarxiv-cs-ai

Environmental Injection Attacks against GUI Agents in Realistic Dynamic Environments

arXiv:2509.11250v3 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) agents are increasingly deployed to interact with online web services, yet their exposure to open-world content

agentsarxiv-cs-cv

ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation

arXiv:2608.21925v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. Howe

Evaluating Human and LLM-Generated Thematic Analysis in HRI for Vulnerable Populations: A Comparative and Ethical Analysis

arXiv:2608.21420v1 Announce Type: new Abstract: Thematic analysis (TA) has long been regarded as an inherently human, reflexive, and interpretive process. However, the extent to which LLM-generated TA

researcharxiv-cs-ro

Evaluating Inference-Time Defenses Against Package Hallucination in LLM-Generated Code

arXiv:2608.22652v1 Announce Type: cross Abstract: LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into

Evaluating Large Language Models for automatic analysis of teacher simulations

arXiv:2407.20360v2 Announce Type: replace Abstract: Digital Simulations (DS) provide safe environments where users interact with an agent through conversational prompts, providing engaging learning ex

Evaluating Multimodal Narrative Understanding of Popular Hollywood Films

arXiv:2608.21430v1 Announce Type: new Abstract: Multimodal language models increasingly show promise for enabling the large-scale computational analysis of film, opening up new avenues for learning ab

Evaluating SAT Solver Metrics as Predictors of Human-Perceived Nonogram Difficulty

arXiv:2608.23300v1 Announce Type: cross Abstract: Algorithmic solver effort is often assumed to align with perceived puzzle difficulty, but this assumption is rarely tested against human solving data.

Evaluating the Efficacy of LLMs to Emulate Realistic Human Personalities

arXiv:2402.14879v2 Announce Type: replace-cross Abstract: To enhance immersion and engagement in video games, the design of Affective Non-Player Characters (ANPCs) is a key focus for researchers and p

Evaluation Awareness in Language Models: Representation, Verbalization, and Control

arXiv:2608.21766v1 Announce Type: cross Abstract: Both capability and safety benchmarks rest upon the assumption that the behavior of language models undergoing a test is informative about their behav

safetyarxiv-cs-ai

Evaluation of Small Vision-Language Models on Qualitative Mechanical Problems

arXiv:2608.22143v1 Announce Type: new Abstract: Qualitative mechanical problem-solving (QMPS) refers to solving qualitative problems from the mechanical domain. Qualitative problems can be solved with

Evidence-State Reliability Under Controlled Degradation: Parser-Validity Divergence in a Multi-Stage LLM Pipeline

arXiv:2608.21559v1 Announce Type: new Abstract: Multi-stage LLM pipelines can remain structurally valid even when evidence available to downstream stages becomes incomplete, compressed, or conflicting

researcharxiv-cs-cl

EviSafe: Evidence-Grounded Safety Evaluation for Vision-Language Models

arXiv:2608.23313v1 Announce Type: new Abstract: Vision-language model safety benchmarks typically evaluate only final responses: whether a model refuses, warns, or complies. This outcome-level view ca

EvoWiki: Incremental State Overwriting and Traceable Question Answering for Cross-Meeting Knowledge Evolution

model-releasesarxiv-cs-cl

arXiv:2608.23265v1 Announce Type: new Abstract: In long-term collaboration spanning multiple meetings, factual states such as decisions and risks are continually revised, overturned, and replaced. Exi

Exact Finite-Length Theory of Uniform Car Parking: Spatial Laws, Absorption, and Aggregation

arXiv:2608.22671v1 Announce Type: new Abstract: The uniform car-parking process is the one-dimensional random sequential adsorption of unit cars on a segment of finite length s: cars arrive at uniform

researcharxiv-cs-ro

Applications

ExecRubrics: Executable Tool-Augmented Rubrics for Verifiable and Efficient Long-Form Evaluation

arXiv:2608.22559v1 Announce Type: new Abstract: Rubrics aim to make language-model evaluation transparent by decomposing response quality into interpretable criteria. However, natural-language rubrics

applicationsarxiv-cs-ai

Expectations and Practices around AI Disclosure in CS Research

arXiv:2608.23271v1 Announce Type: cross Abstract: As generative AI tools find increasing use in research workflows, ongoing debates on their impact, appropriateness and responsible use have led policy

tutorialsarxiv-cs-cl