All entries

everything we build at LangChain is provider/model agnostic for these reasons! our harness is open source and easily customizable!

everything we build at LangChain is provider/model agnostic for these reasons! our harness is open source and easily customizable! On topic: there is a mistake I saw large companies make in late 2025/

agentsharrison-chase--x

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

EvObj: Learning Evolving Object-centric Representations for 3D Instance Segmentation without Scene Supervision

DGX agent

arXiv:2605.13152v1 Announce Type: cross Abstract: We introduce EvObj for unsupervised 3D instance segmentation that bridges the geometric domain gap between synthetic pretraining data and real-world p

applicationsarxiv-cs-ai

14 May 2026

Tutorials

EvoGround: Self-Evolving Video Agents for Video Temporal Grounding

arXiv:2605.13803v1 Announce Type: new Abstract: Video temporal grounding (VTG) takes an untrimmed video and a natural-language query as input and localizes the temporal moment that best matches the qu

tutorialsarxiv-cs-cv

Exact Sequence Interpolation with Transformers

model-releasesarxiv-cs-lg

arXiv:2502.02270v3 Announce Type: replace Abstract: We prove that transformers can exactly interpolate datasets of finite input sequences in R^d, dgeq 2, with corresponding output sequences of smaller

Applications

Exact Verification of Graph Neural Networks with Incremental Constraint Solving

arXiv:2508.09320v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are increasingly often employed in high-stakes applications, such as fraud detection or healthcare, but are susce

applicationsarxiv-cs-ai

Excited to finally get our agent live for the world. A lot of what we’ve learned over time has been condensed and built into the agent so it…

agentscristobal-valenzuela--x

Excited to finally get our agent live for the world. A lot of what we’ve learned over time has been condensed and built into the agent so it can do the best work for you. Meet Runway Agent. Your new A

Excited to see SWE-ZERO trending on HF alongside awesome agentic trace datasets like AgentTrove!

SWE-ZERO and AgentTrove are trending datasets on Hugging Face related to software engineering and agentic AI systems. The post indicates growing interest in trace datasets that capture agent behaviors

agentsclem-delangue--x

Exemplar-Free Continual Learning for State Space Models

arXiv:2505.18604v3 Announce Type: replace Abstract: State-Space Models (SSMs) excel at capturing long-range dependencies with structured recurrence, making them well-suited for sequence modeling. Howe

researcharxiv-cs-lg

Expanded interoperability with Unity Catalog Open APIs

Databricks announced expanded interoperability capabilities for Unity Catalog through open APIs, enabling third-party applications and platforms to integrate with and access Unity Catalog's data gover

industrydatabricks

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion

arXiv:2605.11679v2 Announce Type: replace Abstract: In the realm of multi-objective alignment for large language models, balancing disparate human preferences often manifests as a zero-sum conflict. S

Exploring how EFL students talk to and through AI to develop texts

arXiv:2605.12523v1 Announce Type: cross Abstract: Generative Artificial Intelligence (AI) introduces new considerations for English as a foreign language (EFL) writing pedagogy. This study explores ho

Exploring Human-Robot Collaboration: Analysis of Interaction Modalities in Challenging Tasks

arXiv:2605.13380v1 Announce Type: new Abstract: This work compares three interaction modalities for human-robot collaboration: passive, reactive, and proactive. We studied 18 participants assembling a

researcharxiv-cs-ro

Exploring Multimodal LMMs for Online Episodic Memory Question Answering on the Edge

model-releasesarxiv-cs-cv

arXiv:2602.22455v2 Announce Type: replace Abstract: We investigate the feasibility of using Multimodal Large Language Models (MLLMs) for real-time online episodic memory question answering. While clou

Exploring the holographic entropy cone via reinforcement learning

arXiv:2601.19979v2 Announce Type: replace-cross Abstract: We develop a reinforcement learning algorithm to study the holographic entropy cone. Given a target entropy vector, our algorithm searches for

researcharxiv-cs-lg

Exponential Approximation Rates and Parameter Efficiency of Learnable Bernstein Activations

arXiv:2602.04264v2 Announce Type: replace-cross Abstract: The choice of activation function fundamentally shapes the representational capacity and parameter efficiency of deep neural networks, yet mos

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking

arXiv:2605.12995v1 Announce Type: new Abstract: Traditional retrieval pipelines optimize utility through stages of candidate retrieval and reranking, where ranking operates over a predefined candidate

safetyarxiv-cs-lg

Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm

model-releasesarxiv-cs-cv

arXiv:2605.13402v1 Announce Type: new Abstract: Computing a minimum s-t cut in a graph is a solution to a wide range of computer vision problems, and is often done using the Boykov-Kolmogorov (BK) alg

Fast and effective algorithms for fair clustering at scale

model-releasesarxiv-cs-lg

arXiv:2605.13759v1 Announce Type: new Abstract: Clustering is an unsupervised machine learning task that consists of identifying groups of similar objects. It has numerous applications and is increasi

Local Ai

FeatCal: Feature Calibration for Post-Merging Models

arXiv:2605.13030v1 Announce Type: cross Abstract: Model merging combines task experts into one model and avoids joint training, retraining, or deploying many expert models, but the merged model often

local-aiarxiv-cs-ai

Feature Learning Dynamics in Infinite-Depth Neural Networks

arXiv:2512.21075v2 Announce Type: replace-cross Abstract: Deep neural networks have achieved remarkable success in practice, yet a mechanistic understanding of how features evolve during training rema

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching

model-releasesarxiv-cs-cv

arXiv:2605.13475v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative training of distributed clients while protecting privacy. To enhance generalization capability in FL, prot

FePySR: A Neural Feature Extraction Framework for Efficient and Scalable Symbolic Regression

arXiv:2605.12704v1 Announce Type: cross Abstract: A fundamental challenge in symbolic regression (SR) is efficiently recovering complex mathematical expressions from observational data. Although this

Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit

arXiv:2409.02708v2 Announce Type: replace Abstract: Data scarcity poses a serious threat to modern machine learning and artificial intelligence, as their practical success typically relies on the avai

researcharxiv-cs-lg

Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots

model-releasesarxiv-cs-ro

arXiv:2605.12790v1 Announce Type: new Abstract: Modeling concentric tube robots (CTRs) involves complex nonlinear continuum mechanics, and despite recent progress, physics-based models often lack an a

Figma reports Q1 revenue up 46% YoY to 333.4M, vs. 313.2M est., and forecasts Q2 revenue above estimates, citing AI monetization; FIG jumps 8%+ after hours (Zaheer Kachwala/Reuters)

Zaheer Kachwala / Reuters: Figma reports Q1 revenue up 46% YoY to 333.4M, vs. 313.2M est., and forecasts Q2 revenue above estimates, citing AI monetization; FIG jumps 8%+ after hours — Figma (FIG.N) r

industrytechmeme

Figma stock jumps as first-quarter revenue surges 46% on AI monetization traction

Shares of Figma Inc. rose more than 12% in after-hours trading today after the design software company beat earnings and revenue expectations in its fiscal 2026 first quarter and raised its full-year

industrysiliconangle

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

Filter-then-Weight: Online Data Selection and Reweighting for LLM Fine-Tuning

arXiv:2604.00001v2 Announce Type: replace-cross Abstract: Gradient-based data selection offers a principled framework for estimating sample utility in large language model (LLM) fine-tuning, but exist

Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications

arXiv:2605.13170v1 Announce Type: new Abstract: Multi-agent systems rely on communication for information sharing and action coordination, which exposes a vulnerability to attacks. We investigate sing

agentsarxiv-cs-lg

Fireworks Training Platform continues to expand. Today GLM 5.1 LoRA RL is now live via Training API: SFT, DPO, and full RL on a 200K context…

model-releasesfireworks-ai--x

Fireworks Training Platform continues to expand. Today GLM 5.1 LoRA RL is now live via Training API: SFT, DPO, and full RL on a 200K context window → custom loss functions or smart defaults. No usage

Hardware

FlashSampling: Fast and Memory-Efficient Exact Sampling

arXiv:2603.15854v2 Announce Type: replace-cross Abstract: Sampling from a categorical distribution is mathematically simple, but in large-vocabulary decoding, it often triggers extra memory traffic an

hardwarearxiv-cs-ai

Fleet launches autonomous endpoint management platform to counter AI-accelerated exploits

model-releasessiliconangle

Open device management company Fleet Device Management Inc. today announced its new autonomous endpoint management platform. The company says it shrinks enterprise patch cycles from the industry avera

Hardware

Flow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection

arXiv:2605.13108v1 Announce Type: new Abstract: Face presentation attack detection (FacePAD) remains challenging under diverse spoofing representation, including 2D print and replay, 3D mask-based spo

hardwarearxiv-cs-cv

Flow Matching for Offline Reinforcement Learning with Discrete Actions

arXiv:2602.06138v2 Announce Type: replace Abstract: Generative policies based on diffusion models and flow matching have shown strong promise for offline reinforcement learning (RL), but their applica

safetyarxiv-cs-lg

Flow Matching with Uncertainty Quantification and Guidance

arXiv:2602.10326v2 Announce Type: replace Abstract: Despite the remarkable success of sampling-based generative models such as flow matching, they can still produce samples of inconsistent or degraded

researcharxiv-cs-cv

Applications

FMC-DETR: Frequency-Decoupled Multi-Domain Coordination for Aerial-View Object Detection

arXiv:2509.23056v2 Announce Type: replace Abstract: Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UA

applicationsarxiv-cs-cv

FOAM: Blocked State Folding for Memory-Efficient LLM Training

arXiv:2512.07112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable performance due to their large parameter counts and extensive training data. However

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

Follow the Mean: Reference-Guided Flow Matching [R]

researchr-machinelearning

This paper presents a method for controllable generation in flow matching models by adapting them through reference examples. The key insight is that the velocity field in flow matching is determined

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs

model-releasesarxiv-cs-lg

arXiv:2605.13788v1 Announce Type: new Abstract: Active learning for machine-learning interatomic potentials (MLIPs) must address several challenges to be practical: scaling to large candidate pools, l

Ford stock jumped as much as 25% in two days after the launch of Ford Energy, a new subsidiary providing battery storage capacity to AI data centers (Christian Davies/Financial Times)

Christian Davies / Financial Times: Ford stock jumped as much as 25% in two days after the launch of Ford Energy, a new subsidiary providing battery storage capacity to AI data centers — New subsidiar

industrytechmeme

Formal Conjectures: An Open and Evolving Benchmark for Verified Discovery in Mathematics

arXiv:2605.13171v1 Announce Type: new Abstract: As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their cap

FRAME: Forensic Routing and Adaptive Multi-path Evidence Fusion for Image Manipulation Detection

arXiv:2605.12826v1 Announce Type: cross Abstract: The proliferation of sophisticated image editing tools and generative artificial intelligence models has made verifying the authenticity of digital im

FrameSkip: Learning from Fewer but More Informative Frames in VLA Training

arXiv:2605.13757v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly trained from dense robot demonstration trajectories, often collected through teleoperation, by sampli

safetyarxiv-cs-ro

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation

arXiv:2605.12997v1 Announce Type: new Abstract: Neural operators learn to map initial conditions to the terminal solution of partial differential equations (PDEs), providing a surrogate for the full o

safetyarxiv-cs-lg

Freshworks unveils Freddy AI Agent Studio and MCP Gateway for Freshservice

Freshworks Inc. today unveiled an expanded set of agentic capabilities in its Freshservice information technology service management platform led by a new no-code Freddy AI Agent Studio that lets ente

agentssiliconangle

From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows

arXiv:2603.05093v2 Announce Type: replace-cross Abstract: Feature attributions often hide a critical modeling choice: they explain a prediction along a counterfactual path from a reference state to an

From Generalist to Specialist Representation

arXiv:2605.12733v1 Announce Type: cross Abstract: Given a generalist model, learning a task-relevant specialist representation is fundamental for downstream applications. Identifiability, the asymptot