Search: “framework”

Surgical Video Generation From Diffusion to World Models: A Survey

arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio

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Research

Sycophancy Suppression Can Impair Rational Updating: Anti-Sycophancy Should Preserve the Ability to Update

DGX agent

arXiv:2608.26511v1 Announce Type: new Abstract: Large language models often exhibit sycophancy, revising their answers to align with users when users push back. Such answer flips, however, can arise f

researcharxiv-cs-cl

28 Aug 2026

Task-space model-based control of pneumatic soft actuators

arXiv:2608.27186v1 Announce Type: new Abstract: Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distribu

researcharxiv-cs-ro

TempJail: Temporal Jailbreak Attacks against Image-to-Video Generation Models

model-releasesarxiv-cs-cv

arXiv:2608.26971v1 Announce Type: new Abstract: In recent years, image-to-video (I2V) generation models have made remarkable progress in subject consistency and temporal coherence, enabling high quali

Terrain signatures in Welsh settlement names

arXiv:2608.26978v1 Announce Type: cross Abstract: Landscapes are named, but whether names retain measurable environmental information beyond broad geographic structure is rarely tested. We analysed 3,

researcharxiv-cs-cl

Think3D: Thinking with Space for Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2601.13029v4 Announce Type: replace Abstract: While Vision-Language Models (VLMs) excel at 2D visual understanding, they remain constrained by 2D-centric paradigm that severely limits genuine 3D

Thinking on Shots: Consistent Multi-Shot Video Editing with Agentic Reasoning

arXiv:2608.26809v1 Announce Type: new Abstract: While generative AI has significantly advanced video editing, existing methods primarily focus on single-shot or short video clips. Editing long videos

agentsarxiv-cs-cv

Towards Expert Financial QA via Self-Improving RAG

arXiv:2608.26706v1 Announce Type: new Abstract: Expert-level financial question answering requires both grounded verification to catch numeric hallucinations and audit trails for regulatory compliance

agentsarxiv-cs-cl

Local Ai

TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing

arXiv:2608.26219v1 Announce Type: cross Abstract: Reconstructing continuous physical fields from sparse measurements is central to scientific monitoring, inverse modeling, and digital-twin constructio

local-aiarxiv-cs-lg

TraceBench: Controlled Evaluation of LLM Agents for Time-Series Root-Cause Attribution

model-releasesarxiv-cs-lg

arXiv:2608.27182v1 Announce Type: new Abstract: LLM agents are increasingly applied to anomaly detection and root-cause analysis in time-series observations collected from real-world systems; however,

TreeGraft: Adaptive Multi-Drafter Grafting for Tree-Based Speculative Decoding

arXiv:2608.26112v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference through a draft-then-verify paradigm. Building on this, tree-structured methods improve

researcharxiv-cs-cl

UCB for Large-Scale Pure Exploration: Beyond Sub-Gaussianity

arXiv:2511.22273v2 Announce Type: replace-cross Abstract: Selecting the best alternative from a finite set is the central objective of ranking and selection (R&S) and best arm identification (BAI). Tr

UFO-DETR: Frequency-Guided End-to-End Detector for UAV Tiny Objects

arXiv:2602.22712v2 Announce Type: replace Abstract: Small target detection in UAV imagery faces significant challenges such as scale variations, dense distribution, and the dominance of small targets.

Unifying Detection and Adaptation in Task-Free Continual Learning

model-releasesarxiv-cs-cl

arXiv:2608.27070v1 Announce Type: cross Abstract: To mitigate catastrophic forgetting in downstream continual learning (CL) for large language models (LLMs), existing methods typically constrain param

Local Ai

UniGeo: A Multi-modal Large Language Model for Text-Guided Cross-View Geo-Localization

arXiv:2608.26722v1 Announce Type: new Abstract: Text-guided drone geo-localization aims to identify a target region in a large-scale image gallery from a natural-language description. Existing methods

local-aiarxiv-cs-cv

Verify Smarter, Evolve Further: Efficient Harness Evolution through Behavior-Aware Verification

arXiv:2608.27311v1 Announce Type: new Abstract: Agent harnesses shape how language-model agents use instructions, tools, and runtime components, but adapting these harnesses requires costly verificati

agentsarxiv-cs-ai

VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation

arXiv:2608.26155v1 Announce Type: cross Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limi

safetyarxiv-cs-ai

Video-FLAIR: Not Whether to Reason, But How

arXiv:2608.26495v1 Announce Type: new Abstract: Multimodal queries can require different types of reasoning. Some can be answered via perceptual reasoning, extracting information directly from the vis

Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

arXiv:2608.27065v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has recently emerged as an effective post-training paradigm that improves policy optimization through dense token-lev

Virtual iEEG from Scalp EEG: Charting the Landscape of Source Imaging, Intracranial Inference and Reconstruction

arXiv:2608.26998v1 Announce Type: new Abstract: Intracranial electroencephalography (iEEG) provides temporally precise and spatially specific access to neural activity from focal and deep brain region

When Interference Graphs Evolve: Doubly Robust Estimation of Dynamic Peer Effects

arXiv:2608.27187v1 Announce Type: new Abstract: Peer effects are difficult to estimate when interaction graphs evolve because pre-assignment network history, dynamic peer exposure, and post-assignment

When Privacy Hurts Mergeability: Geometry-Aware Model Merging under Differential Privacy

model-releasesarxiv-cs-lg

arXiv:2608.26655v1 Announce Type: new Abstract: Model merging promises to construct a single multi-task model from independently fine-tuned task models without accessing the original task data. This m

When the Canonical Completion Is Wrong: Formalizing and Measuring the Jump in Large Language Models

arXiv:2608.26187v1 Announce Type: cross Abstract: Whether large language models (LLMs) can perform the abductive leap from evidence to a new system of axioms, commonly referred to as a jump, has recen

researcharxiv-cs-ai

When Tool Outputs Become Commands: Separating Action Induction from Runtime Authorization in Tool-Augmented LLM Agents

arXiv:2608.27146v1 Announce Type: new Abstract: Tool-augmented LLM agents must rely on untrusted runtime Observations to complete open-ended tasks; however, when tool outputs no longer merely provide

agentsarxiv-cs-ai

WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution

model-releasesarxiv-cs-ai

arXiv:2608.27454v1 Announce Type: new Abstract: Agent skills package specialized knowledge and workflows into reusable resources that extend AI agent capabilities. Recent work automatically discovers

Applications

3DGS-HPC: Distractor-free 3D Gaussian Splatting with Hybrid Patch-wise Classification

arXiv:2603.07587v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in novel view synthesis and 3D scene reconstruction, but its quality often degr

applicationsarxiv-cs-cv

Adaptive Triggering for Bias Correction in LLM Reasoning

arXiv:2608.25379v1 Announce Type: new Abstract: Chain-of-thought prompting can expose and amplify demographic stereotypes within an LLM's intermediate reasoning and create a failure mode that final-an

safetyarxiv-cs-cl

AdaptiveEmbed: Sample-Adaptive Multi-Vector Representation for Multimodal Retrieval

arXiv:2608.25412v1 Announce Type: new Abstract: Multi-vector representations have emerged as an effective paradigm for multimodal retrieval, representing each sample with multiple complementary embedd

Applications

Addressing the Reasoning Gap: Mechanistic Circuit-Based Knowledge Editing in Large Language Models

arXiv:2604.05876v2 Announce Type: replace Abstract: Deploying Large Language Models (LLMs) in real-world dynamic environments raises the challenge of updating their pre-trained knowledge. While existi

applicationsarxiv-cs-cl

AERIS: Offline Policy Improvement for Multi-UAV Integrated Sensing and Communication

arXiv:2608.25477v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) is a promising 6G paradigm, but dynamic multi-UAV ISAC control must

safetyarxiv-cs-lg

AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models

model-releasesarxiv-cs-lg

arXiv:2510.15987v3 Announce Type: replace Abstract: How do inference time and latent computations enable large language models (LLMs) to solve multi-step reasoning problems? We introduce AlgoTrace, a

Applications

Are LLM-Enhanced GNNs Privacy-Safe?

arXiv:2608.25727v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced graph neural networks (GNNs) by enriching node representations with semantic information, giving ris

applicationsarxiv-cs-lg

Asymmetric Cross-Modal Fine-Grained Visual Categorization: ACF-Net and the BirdPro Benchmark

model-releasesarxiv-cs-cv

arXiv:2608.25520v1 Announce Type: new Abstract: Audio-visual cross-modal Fine-Grained Visual Categorization (FGVC) aims to identify fine-grained categories by jointly leveraging visual and auditory in

Tutorials

Bayesian Flow Networks for Offline Trajectory Planning

arXiv:2608.25163v1 Announce Type: new Abstract: Offline reinforcement learning (RL) leverages static datasets to learn decision policies without real-time environment interaction. While recent sequenc

tutorialsarxiv-cs-lg

Behind the [MASK]: Disentangling Representation and Faithfulness in DAPF-Based Dementia Detection

arXiv:2608.25028v1 Announce Type: new Abstract: Spoken-language analysis via prompt-based domain-adaptive models is a promising direction for low-resource, non-invasive dementia screening, but such mo

researcharxiv-cs-cl

Beyond Local Surprise: Grounded Dialogue as Selective Belief Revision under Referential Uncertainty

arXiv:2608.26035v1 Announce Type: new Abstract: When a speaker refers to a scene that the listener cannot directly see, the listener must decide whether to preserve its current understanding or revise

safetyarxiv-cs-cl

Beyond Pairwise Feedback: Listwise Vision-Language Supervision for Preference-Based Reward Learning

arXiv:2608.25350v1 Announce Type: new Abstract: Vision-language models (VLMs) have emerged as a powerful source of supervision for reinforcement learning, enabling agents to leverage rich semantic kno

Beyond Scaling: Self-Evolving LLM Agents for Hardware Kernel Optimization via an Experience-Driven Workflow and Experience Graph Memory

arXiv:2608.25570v1 Announce Type: new Abstract: Hardware kernel optimization requires repeated compilation, correctness testing, profiling, and revision. LLM agents can automate parts of this process,

agentsarxiv-cs-lg

Bidirectional Temporal Dynamics Modeling for EEG-based Driving Fatigue Recognition

arXiv:2602.14071v3 Announce Type: replace-cross Abstract: Driving fatigue is a major contributor to traffic accidents and poses a serious threat to road safety. Electroencephalography (EEG) provides a

Bootstrapping a 4D LiDAR Annotation Tool from Video Foundation Models

arXiv:2608.25418v1 Announce Type: new Abstract: Progress in 4D LiDAR segmentation is bottlenecked by data. Assigning temporally consistent labels across sparse point cloud sequences is costly and hard

BVR Sim: An Open and High-Throughput Environment for Heterogeneous Air-Combat Reinforcement Learning

arXiv:2608.25419v1 Announce Type: cross Abstract: Beyond-visual-range (BVR) air combat is a challenging reinforcement-learning domain characterized by partial observability, long-horizon decision maki

safetyarxiv-cs-lg

Capacity Overflow: A Blind Spot for Backdoor Attacks in Vision MoE

arXiv:2608.25371v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent paradigm for scaling Vision Transformers efficiently. To ensure computational scalability and prevent ex

CaSKG: Counterfactual-Causal Skill Graphs for Scalable Agent Skill Retrieval

model-releasesarxiv-cs-cl

arXiv:2608.25500v1 Announce Type: cross Abstract: Reusable skill libraries allow large language model (LLM) agents to reuse procedural knowledge across tasks, but they also turn memory access into a c

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future

safetyarxiv-cs-lg

Local Ai

CloSeR: Unified Relational Distillation from Closed-Set Teachers for Category Discovery

arXiv:2608.25692v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) is an intriguing open-world problem that has garnered increasing attention: given partially labelled data, the goal

local-aiarxiv-cs-cv

ClueWeaver: Reward-Guided Dual-Agent Evidence Reasoning for Compact LLMs on Literary Long Narratives

arXiv:2608.25531v1 Announce Type: new Abstract: Humanities and social science research requires close reading of long narrative materials such as novels, scripts, archives, and case reports, yet many

agentsarxiv-cs-cl

Cluster-Dags as Powerful Background Knowledge For Causal Discovery

arXiv:2512.10032v3 Announce Type: replace Abstract: Finding cause-effect relationships is of key importance in science. Causal discovery aims to recover a graph from data that succinctly describes the

Code World Model: Coding Agent as World Brain

arXiv:2608.25927v1 Announce Type: cross Abstract: World models aim to simulate how complex environments evolve under actions and events, yet existing video-based world models primarily learn dynamics

agentsarxiv-cs-cl