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SULAND v2: A Refined RGB Dataset and Deep Learning Object Detection Benchmark for UAV/UGV-Based SUrface LANDmine Detection Under Domain Shift

model-releasesarxiv-cs-cv

arXiv:2607.28996v1 Announce Type: new Abstract: RGB imagery offers a practical, low-cost option for Unmanned Aerial/Ground Vehicle (UAV/UGV) survey support in surface-landmine detection, but object de

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Research

Sycophancy Undermines Epistemic Vigilance in Cooperative Vision-Language Tasks

DGX agent

arXiv:2607.29585v1 Announce Type: new Abstract: To maintain common ground in cooperative conversation, humans iteratively update their beliefs as conversation participants share new information; parti

researcharxiv-cs-cl

3 Aug 2026

Symplectic Representation of Legendre Dynamics

arXiv:2512.19409v2 Announce Type: replace Abstract: Modern learning systems act on internal representations of data, yet how these representations encode underlying physical or statistical structure i

researcharxiv-cs-lg

Local Ai

TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction

arXiv:2607.29231v1 Announce Type: new Abstract: Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile s

local-aiarxiv-cs-ro

TAGTorch: A PyTorch Library for Geometry, Topology, and Symmetry-Aware Machine Learning

arXiv:2607.28755v1 Announce Type: new Abstract: Over the last decade, neural networks have been applied to an increasingly diverse range of applications, including data with rich geometric, topologica

researcharxiv-cs-lg

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter

model-releasesarxiv-cs-ai

arXiv:2607.28657v1 Announce Type: new Abstract: Large Language Models (LLMs) often require carefully crafted prompts to unlock their full potential, which can be a barrier for non-expert users. This w

TAVI-TEC: An AI-Based Tool for Procedural Planning of Transcatheter Aortic Valve Implantation

arXiv:2607.29243v1 Announce Type: cross Abstract: Computed tomography angiography (CTA) is crucial for preprocedural TAVI planning, providing the anatomical information required for prosthesis sizing

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

model-releasesarxiv-cs-cv

arXiv:2605.25333v2 Announce Type: replace Abstract: Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption.

Technological Advances in Detecting and Managing Cognitive Impairment in Older Adults: Trends, Challenges, and Future Directions

arXiv:2607.28687v1 Announce Type: cross Abstract: As populations age, cognitive decline from mild cognitive impairment (MCI) to dementia is a defining health challenge of the coming decades, yet routi

TELLER: Dual-Path Iterative Preference Optimization for Table Entity Linking

arXiv:2607.28680v1 Announce Type: new Abstract: Entity linking in tables matches short and ambiguous cell mentions to their corresponding knowledge-base entities. Existing approaches typically rely on

safetyarxiv-cs-cl

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration

arXiv:2607.29482v1 Announce Type: new Abstract: By relying on independent couplings from uninformative Gaussian priors, standard diffusion and flow matching models are forced to learn complex, high-co

safetyarxiv-cs-ro

Tensor Data Scattering and the Impossibility of Slicing Theorem

arXiv:2012.01982v3 Announce Type: replace Abstract: This paper proposes a standard way to represent sparse tensors. A broad theoretical framework for tensor data scattering methods used in various dee

researcharxiv-cs-lg

TerraNova: A Foundation Model for the Anthropocene

arXiv:2607.29527v1 Announce Type: cross Abstract: A defining problem of the Anthropocene is to model the physical Earth and human societies as one coupled system, yet no learned representation spans t

TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text

arXiv:2607.28862v1 Announce Type: cross Abstract: The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously rais

TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion

arXiv:2607.29459v1 Announce Type: cross Abstract: Large-scale multivariate time series from heterogeneous IoT sensors demand accurate long-term forecasting for resource scheduling and predictive maint

The Asymmetric Effects of Knowledge Distillation on Bias in Small Language Models

model-releasesarxiv-cs-ai

arXiv:2607.28639v1 Announce Type: cross Abstract: We show that knowledge distillation in small instruction-tuned language models has asymmetric effects on bias. On unambiguous tasks (BBQ-disambig), re

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale

arXiv:2607.14144v2 Announce Type: replace Abstract: The Platonic Representation Hypothesis (PRH) holds that as models scale, representations of heterogeneous networks converge toward a shared model of

Applications

The Checking Problem: What must be true before AI ships in a regulated firm

arXiv:2607.28666v1 Announce Type: new Abstract: Enterprise AI programmes stall at a rate that is widely quoted and poorly explained. This paper measures the mechanism. Six document-heavy workflows of

applicationsarxiv-cs-cl

Agents

The Formalism Trap: Are LLM-as-a-Judge Evaluators Blinded by Consensus Mimicry under Social Load?

arXiv:2607.28641v1 Announce Type: cross Abstract: We introduce the extit{Agentic Formalism Trap} and the Evaluative Dissonance Index (D_E), quantifying how LLM-as-a-Judge systems conflate structural p

agentsarxiv-cs-ai

The Greedy Advantage in Finite-Horizon Bandits

arXiv:2607.29375v1 Announce Type: cross Abstract: Organizations increasingly rely on sequential experimentation to improve decision-making. While the multi-armed bandit literature has developed algori

safetyarxiv-cs-lg

The Grokked Illusion: True Equilibrium Mitigates Catastrophic Forgetting

model-releasesarxiv-cs-lg

arXiv:2607.29503v1 Announce Type: new Abstract: While neural networks are typically evaluated by their training and test performance, these metrics do not reveal how robust a learned representation is

The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection

arXiv:2607.29541v1 Announce Type: new Abstract: In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while benefici

safetyarxiv-cs-cv

The Morphological Core of Dungan: A Two-Dialect Finite-State Model and a Multi-Genre Evaluation

model-releasesarxiv-cs-cl

arXiv:2607.28766v1 Announce Type: new Abstract: Dungan, a Sinitic language of Central Asia written in a Cyrillic-based script, is described in detail in the grammatical literature, yet the quantitativ

The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs

model-releasesarxiv-cs-lg

arXiv:2607.29601v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts large language models using a single shared Low-Rank Adapter (LoRA). This shared optimization spa

The persuasive power of large language models does not depend on their perceived national origin

arXiv:2607.29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as fo

The Theoretical Foundation of Socratic Tests: Dynamic, Multimodal, Conversational Examinations

arXiv:2607.29624v1 Announce Type: cross Abstract: Traditional static assessments rely on a subtractive, deficit-based grading model that often penalizes ambition and obscures diagnostic feedback. Conv

ThinkReset: Learnable Intermediate Interface Construction for Bounded-Context Long-Horizon Reasoning

arXiv:2607.28642v1 Announce Type: new Abstract: Long chain-of-thought reasoning improves performance on complex problems, but it also introduces redundancy accumulation, context overflow, and error an

Tutorials

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces

arXiv:2308.08794v4 Announce Type: replace Abstract: Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems. For instance, i

tutorialsarxiv-cs-lg

To Add Is Machine, To Delete Is Human: Measuring and Mitigating Deletion Avoidance in LLM Code Editing

model-releasesarxiv-cs-ai

arXiv:2607.28887v1 Announce Type: cross Abstract: Large language models increasingly write and repair production code, yet evidence is mounting that their test-passing patches leave codebases harder t

Tutorials

To Facilitate or not to Facilitate: Human and LLM Facilitator Tendencies in Online Discussions

arXiv:2607.28643v1 Announce Type: cross Abstract: Automating facilitation in online discussions is a long-standing social concern given the increasing time we spend on online spaces and the failure of

tutorialsarxiv-cs-cl

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

researcharxiv-cs-cl

Tokenizer-Agnostic Engram Module

model-releasesarxiv-cs-cl

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

Tokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR

arXiv:2607.09598v2 Announce Type: replace Abstract: Lightweight speech recognition models are critical for edge deployment, yet highly optimized architectures like Moonshine often fail on morphologica

researcharxiv-cs-cl

TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ

researcharxiv-cs-cl

Hardware

TokTier: Exact Stateful Tokenization for Agentic LLM Serving

arXiv:2607.29678v1 Announce Type: new Abstract: LLM serving systems cache prompt KV state, yet most front ends still re-tokenize the full request text on every call. The cost lands on coding agents, w

hardwarearxiv-cs-cl

Tutorials

TOOD: Task-Aware Out-of-Distribution Score Calibration for Continual Learners

arXiv:2607.29592v1 Announce Type: new Abstract: The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly impor

tutorialsarxiv-cs-cv

Tool Specifications Matter: Uncovering and Mitigating Safety Risks in AI Agents

arXiv:2607.29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential

Hardware

Topology-Aware Data Movement for Disaggregated GPU Inference

arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate

hardwarearxiv-cs-ai

TORUS: A Test of Rendering-Understanding Self-Coherence for Unified Audio Models

arXiv:2607.28896v1 Announce Type: cross Abstract: Unified audio models capable of audio understanding, audio generation and, increasingly, audio editing are proliferating rapidly. Yet a basic question

Toward Robust and 3D-Aware RGB-NIR Imaging in the Dark

arXiv:2607.29684v1 Announce Type: new Abstract: Robust low-light imaging remains challenging for the community. Recent studies have explored fusing Near-Infrared (NIR) with noisy RGB to achieve improv

researcharxiv-cs-cv

Applications

Towards Automated Initial Probe Placement in Transthoracic Teleultrasound Using Human Mesh and Skeleton Recovery

arXiv:2603.11257v2 Announce Type: replace Abstract: Cardiac and lung ultrasound are technically demanding because operators must identify patient-specific intercostal acoustic windows and then navigat

applicationsarxiv-cs-cv

Towards bridging the gap: Systematic sim-to-real transfer for diverse legged robots

model-releasesarxiv-cs-ro

arXiv:2509.06342v2 Announce Type: replace Abstract: Legged robots must achieve both robust locomotion and energy efficiency to be practical in real-world environments. Yet controllers trained in simul

Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation

arXiv:2601.22546v2 Announce Type: replace-cross Abstract: The recent advancements in Large Language Models (LLMs) have attracted interest in exploring their in-context learning abilities and chain-of-

Applications

Towards White-Box Deep Wireless Sensing

arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep

applicationsarxiv-cs-ai

TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking

arXiv:2604.01207v2 Announce Type: replace Abstract: Existing 3D Gaussian Splatting (3DGS) editing methods primarily focus on appearance modification and often struggle to support flexible geometry edi

safetyarxiv-cs-cv

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

TRACT: Temporally Routed Action Chunks with Chronological Phase Authority for Contact-Rich Manipulation

arXiv:2607.29285v1 Announce Type: new Abstract: Action chunking shortens the effective decision horizon of robot imitation learning by predicting multiple future actions, while conventional phase cond

safetyarxiv-cs-ro

Training-Free Entity-Level Few-Shot Segmentation of Remote Sensing Images with Advection Refinement

arXiv:2607.29278v1 Announce Type: new Abstract: Existing cross-domain few-shot segmentation approaches suffer from high training costs due to source-domain episodic training and pixel-wise dense predi

researcharxiv-cs-cv