All entries

arXiv:2604.17714v1 Announce Type: new Abstract: LLM confidence signals are used for abstention, routing, and safety-critical decisions. No standard practice exists for checking whether a confidence si

arXiv:2602.19549v2 Announce Type: replace Abstract: Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current

Security Agent builds on Replit Agent’s always-on security, which scans for vulnerabilities and audits dependencies as you build, before anything goes live. Read details here: https://blog.replit.com/

arXiv:2604.16562v1 Announce Type: new Abstract: Generalizable gaze estimation methods have garnered increasing attention due to their critical importance in real-world applications and have achieved s

arXiv:2604.17252v1 Announce Type: new Abstract: Recent advancements in large language models (LLMs) have enabled agents to tackle complex embodied tasks through environmental interaction. However, the

arXiv:2604.17143v1 Announce Type: new Abstract: Despite their substantial successes, AI agents continue to face fundamental challenges in terms of trustworthiness. Consider deep research agents, taske

arXiv:2604.17451v1 Announce Type: new Abstract: Increasingly advanced data augmentation techniques have greatly aided clinical medical research, increasing data diversity and improving model generaliz

arXiv:2604.17433v1 Announce Type: new Abstract: Self-consistency (SC) is a popular technique for improving the reasoning accuracy of large language models by aggregating multiple sampled outputs, but

arXiv:2411.15115v3 Announce Type: replace-cross Abstract: Recent text-to-video (T2V) diffusion models have made remarkable progress in generating high-quality videos. However, they often struggle to a

arXiv:2506.10137v3 Announce Type: replace Abstract: While goal-conditioned behavior cloning (GCBC) methods can perform well on in-distribution training tasks, they do not necessarily generalize zero-s

arXiv:2604.16958v1 Announce Type: new Abstract: Narrative-driven product photography has become a prevalent paradigm in modern marketing, as coherent visual storytelling helps convey product value and

arXiv:2604.16817v1 Announce Type: new Abstract: Imbalanced data is commonly present in real-world applications. While data synthesis can effectively mitigate the data scarcity problem of rare-classes,

arXiv:2604.17652v1 Announce Type: new Abstract: Sentinel-5P (S5P) plays a critical role in atmospheric monitoring; however, its spatial resolution limits fine-scale analysis. Existing super-resolution

arXiv:2604.18237v1 Announce Type: new Abstract: In large-scale distributed scenarios, increasingly complex tasks demand more intelligent collaboration across networks, requiring the joint extraction o

arXiv:2604.17659v1 Announce Type: new Abstract: We introduce the Semantic Density Effect (SDE): the empirical finding that prompts carrying higher semantic information per token consistently produce m

arXiv:2604.18464v1 Announce Type: new Abstract: Semantic Tube Prediction (STP) leverages representation geometric to regularize LLM hidden-state trajectories toward locally linear geodesics during fin

arXiv:2604.16500v1 Announce Type: new Abstract: The reliable computational assessment of photographic composition requires features that are discriminative of spatial layout yet robust to semantic con

arXiv:2604.18476v1 Announce Type: new Abstract: Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily

arXiv:2510.02034v2 Announce Type: replace Abstract: We introduce METHODNAME, a novel framework for semantic-aware 3D shape and texture morphing directly from multi-view images. While 3D Gaussian Splat

Sen. Warren: 'Did Donald Trump lose the 2020 election?' Handsome Kevin: 'ummm... errr... ' His response raises real questions about whether Warsh is independent of the President and if he has the cour

arXiv:2505.13353v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed for understanding large codebases, but whether they understand operational semantics of long

arXiv:2505.19237v2 Announce Type: replace-cross Abstract: Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, auto

arXiv:2604.02908v2 Announce Type: replace Abstract: We present SentiAvatar, a framework for building expressive interactive 3D digital humans, and use it to create SuSu, a virtual character that speak

arXiv:2601.09515v2 Announce Type: replace Abstract: Due to the dynamically evolving nature of real-world query streams, relevance models struggle to generalize to practical search scenarios. A sophist

arXiv:2604.18580v1 Announce Type: cross Abstract: Modern sequence models are dominated by Transformers, where self-attention mixes information from the visible context in an input-dependent way. Howev

arXiv:2604.16362v1 Announce Type: cross Abstract: Data scarcity and weak supervision continue to limit the performance of machine learning models in many real-world applications, such as mammography,

arXiv:2410.05248v4 Announce Type: replace Abstract: To acquire instruction-following capabilities, large language models (LLMs) undergo instruction tuning, where they are trained on instruction-respon

Share this with your representative! https://huggingface.co/blog/cybersecurity-openness I’m hearing there’s renewed lobbying in DC and in state legislatures to ban or severely restrict open-source. Li

arXiv:2604.17865v1 Announce Type: new Abstract: Automated polyp segmentation is critical for early colorectal cancer detection and its prevention, yet remains challenging due to weak boundaries, large

arXiv:2604.17189v1 Announce Type: new Abstract: In this study, we propose a new sheepdog-inspired control method for a swarm of small unmanned aerial vehicles (UAVs), which predicts the swarm behavior

arXiv:2604.16423v1 Announce Type: new Abstract: Defensive training methods such as positive preventative steering (PPS) and inoculation prompting (IP) offer surprising results through seemingly simila

arXiv:2511.10370v2 Announce Type: replace Abstract: Geospatial foundation models (GFMs) for Earth observation often fail to perform reliably in environments underrepresented during pretraining. We int

arXiv:2604.17041v1 Announce Type: new Abstract: The public accessibility of large vision-language models (LVLMs) raises serious concerns about unauthorized model reuse and intellectual property infrin

arXiv:2604.17324v1 Announce Type: new Abstract: Graph transformers achieve strong results on molecular and long-range reasoning tasks, yet remain hampered by over-smoothing (the progressive collapse o

arXiv:2602.22913v2 Announce Type: replace-cross Abstract: With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems

arXiv:2604.18034v1 Announce Type: new Abstract: We present SignDPO, a novel multi-level Direct Preference Optimisation (DPO) framework designed to enhance the alignment of skeleton-based Sign Language

Since this is blowing up on hacker news. Boris said that CLI usage is allowed. Thus we added support for it, only to find out that we are still blocked there. It is trival to work around with a few re

arXiv:2604.16842v1 Announce Type: cross Abstract: This thesis develops numerical and theoretical approaches for understanding and analyzing singularity formation in Partial Differential Equations (PDE

arXiv:2604.16883v1 Announce Type: new Abstract: In long-context decoding for LLMs and LMMs, attention becomes increasingly memory-bound because each decoding step must load a large amount of KV-cache

arXiv:2604.04804v2 Announce Type: replace Abstract: Learning from experience is critical for building capable large language model (LLM) agents, yet prevailing self-evolving paradigms remain inefficie

arXiv:2603.13740v3 Announce Type: replace Abstract: We introduce Sky2Ground, a three-view dataset designed for varying altitude camera localization, correspondence learning, and reconstruction. The da

ChatGPT's updated image generation capabilities (Images 2.0) can now create visual content in presentation formats, including slides and infographics, as demonstrated by user @yuguang_yang. This enhan

arXiv:2604.17627v1 Announce Type: new Abstract: Serving large language models under latency service-level objectives (SLOs) is a configuration-heavy systems problem with an unusually failure-prone sea

arXiv:2411.09593v2 Announce Type: replace-cross Abstract: The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesosco

arXiv:2604.16517v1 Announce Type: cross Abstract: Large vision-language models (VLMs) achieve strong performance on multimodal tasks but often suffer from hallucination and poor grounding in knowledge

Snowflake Inc. is expanding its push into enterprise artificial intelligence with a set of updates to its Snowflake Intelligence and Cortex Code offerings, positioning its platform as a centralized co