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Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning

arXiv:2607.23837v1 Announce Type: cross Abstract: Large language models generalize well to individual tasks but lack an inherent mechanism for learning them sequentially, leading to catastrophic forge

researcharxiv-cs-cl

Layering Virtual Try-On

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DGX agent

arXiv:2607.22924v1 Announce Type: new Abstract: In the real world, fashion is about layering: adding a jacket over a shirt, or a sequence of adding and removing layers, rather than just a single-layer

model-releasesarxiv-cs-cv

28 Jul 2026

LazyMem: Retrieve Broadly, Construct Selectively for Efficient Long-Term Agent Memory

arXiv:2607.22690v1 Announce Type: new Abstract: Long-term memory lets LLM agents reuse past interactions, but raw dialogue histories are verbose and information-sparse. Retrieving broadly improves evi

LC-SEPLM: long-range contact-supervised adaptation for sequence-only protein representation learning

arXiv:2607.22777v1 Announce Type: cross Abstract: Protein language models learn transferable sequence representations. However, because they primarily model contextual dependencies along amino-acid se

LCMamNet: A Lightweight Cross-scale Mamba Network for Infrared Small Target Detection

arXiv:2607.24184v1 Announce Type: new Abstract: Infrared small target detection (IRSTD) is important for low-altitude perception, unmanned-system warning, and security monitoring. However, weak target

local-aiarxiv-cs-cv

LEACL: LLM-Enhanced Automatic Curriculum Learning for Reinforcement Learning in Long-Horizon Manipulation Tasks

model-releasesarxiv-cs-ro

arXiv:2607.23515v1 Announce Type: new Abstract: Long-horizon manipulation tasks pose significant challenges for reinforcement learning due to sparse reward signals and long horizons. Automatic curricu

LeapBot-WA: World-Anchor Action Models via Predictive Latent Alignments

arXiv:2607.23969v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a powerful paradigm for embodied intelligence, yet the prevailing reliance on pixel-level video generation cr

safetyarxiv-cs-ro

Learned Interventions in Lean 4 grind

arXiv:2607.22972v1 Announce Type: new Abstract: Lean~4's grind{} tactic combines congruence closure, ematch{}ing, and case-splitting into a single automated solver, and like any such solver, it relies

tutorialsarxiv-cs-lg

Learning Adaptive Multi-Task Guidance, Navigation, and Control via Hypernetworks

arXiv:2607.24292v1 Announce Type: new Abstract: Autonomous free-flying robots in orbital environments require controllers that are both versatile and resource-efficient, yet maintaining a separate, ta

safetyarxiv-cs-ro

Learning Asymptotics with Convergence-Rate Guarantees using Linear Least Squares

arXiv:2607.23287v1 Announce Type: cross Abstract: We introduce a new research area that is called Asymptotics Learning Theory (ALT) and combines optimization with asymptotic analysis. In particular, A

Learning-based Hierarchical Tracheal Anatomy Understanding from Sparse Surgical Demonstration Annotations for Ultrasound Robots

arXiv:2607.22789v1 Announce Type: cross Abstract: Tracheostomy requires precise localization of the tracheal incision site; however, conventional manual palpation is subjective and often unreliable, w

local-aiarxiv-cs-cv

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones

arXiv:2607.22803v1 Announce Type: cross Abstract: Recovering the 6-DoF pose of the knee bones from a plain radiograph, given the patient's segmented pre-operative CT, turns a routine low-dose image in

tutorialsarxiv-cs-cv

Learning Distributions from Multiple Data Providers

arXiv:2607.24732v1 Announce Type: cross Abstract: Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditiona

tutorialsarxiv-cs-lg

Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided Holder Regularity

arXiv:2607.22906v1 Announce Type: new Abstract: We study adaptive gradient descent for continuously differentiable, possibly nonconvex objectives under one-sided Holder regularity. Unlike classical Ho

Learning Reusable Hybrid Motion Priors for Humanoid Locomotion from Motion Imitation

arXiv:2607.24083v1 Announce Type: new Abstract: Reinforcement learning can produce robust humanoid controllers, but each new task is typically trained as a separate policy with its own reward design a

safetyarxiv-cs-lg

Learning Sampling Parameters for Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2607.23488v1 Announce Type: cross Abstract: Text-to-image diffusion models expose many inference-time sampling parameters, including prompts, negative prompts, classifier-free guidance scales, a

Learning switched non-linear dynamical systems from a single trajectory

arXiv:2607.23502v1 Announce Type: cross Abstract: We study empirical risk minimization for learning non-linear dynamical systems whose transition dynamics may switch over time. Under stability assumpt

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence

arXiv:2607.22748v1 Announce Type: cross Abstract: Modern neural networks primarily adapt through parameter modification within predefined computational structures. While recent methods introduce modul

Learning to Optimize at Scale: A Benders Decomposition-TransfORmers Framework for Stochastic Combinatorial Optimization

arXiv:2607.22550v1 Announce Type: cross Abstract: We propose a learning-augmented Benders decomposition framework to solve large-scale two-stage stochastic mixed-integer programs. We focus on the two-

Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks

arXiv:2607.23467v1 Announce Type: new Abstract: We study an integrated pickup-and-delivery problem on sparse, non-Euclidean networks that jointly optimizes cyclic routing, cargo flow allocation, and c

Agents

Learning Traversability-Aware Global Planners for Long Horizon Off-Road Navigation

arXiv:2607.23743v1 Announce Type: new Abstract: Autonomous navigation across large off-road environments remains a challenging problem. Onboard sensors perceive only the immediate surroundings, yet sa

agentsarxiv-cs-ro

Applications

Learning When to Reason for Text-to-SQL via SFT and DPO

arXiv:2607.22622v1 Announce Type: cross Abstract: Recent Text-to-SQL methods rely heavily on reasoning-centric paradigms such as Chain-of-Thought (CoT), achieving substantial gains on complex benchmar

applicationsarxiv-cs-ai

LEDOM: Reverse Language Model

arXiv:2507.01335v4 Announce Type: replace-cross Abstract: Autoregressive language models are trained exclusively left-to-right. We explore the complementary factorization, training right-to-left at sc

researcharxiv-cs-ai

LEGO Co-builder: Exploring Fine-Grained Vision-Language Modeling for Multimodal LEGO Assembly Assistants

arXiv:2507.05515v4 Announce Type: replace Abstract: Vision-language models (VLMs) are facing the challenges of understanding and following multimodal assembly instructions, particularly when fine-grai

Let AI Agents Translate Networks, Not Reason About Them

arXiv:2607.22947v1 Announce Type: new Abstract: A formal model enables verifying reachability, localizing an outage, or anticipating the blast radius of a change. Yet, virtually no production network

local-aiarxiv-cs-ai

Applications

Let Me Look at You: Advanced Facial Expression Modeling for Conversational Speech Synthesis

arXiv:2607.24430v1 Announce Type: cross Abstract: Conversational Speech Synthesis is a fundamental component of human-computer interaction, aiming to generate contextually appropriate, expressive, and

applicationsarxiv-cs-cl

LEX-EC: A Lexical Evidence-Channel Audit Framework for Zero-Shot LLM Personality Classification in Black-Box Settings

arXiv:2607.24435v1 Announce Type: cross Abstract: Large language models may easily assign personality labels from text, but model interpretability remains an open problem. To address this gap, we intr

researcharxiv-cs-ai

Agents

Lexical discovery in unknown environments orchestrated by Large Language Models

arXiv:2607.22591v1 Announce Type: new Abstract: Populations of autonomous agents deployed in unknown environments (e.g. planetary or deep-sea exploration) must develop shared vocabularies to refer to

agentsarxiv-cs-ai

LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

arXiv:2411.00918v5 Announce Type: replace-cross Abstract: Mixture of experts (MoE) architectures have become a cornerstone for scaling up and are a key component in most large language models such as

Like a Baby: Visually Situated Neural Language Acquisition

arXiv:1805.11546v3 Announce Type: replace-cross Abstract: We examine the benefits of visual context in training neural language models to perform next-word prediction. A multi-modal neural architectur

tutorialsarxiv-cs-ai

Like a bilingual baby: The advantage of visually grounding a bilingual language model

arXiv:2210.05487v3 Announce Type: replace Abstract: Unlike most neural language models, humans learn language in a rich, multi-sensory and, often, multi-lingual environment. Current language models ty

tutorialsarxiv-cs-cl

Agents

Limbomorphs

arXiv:2607.23842v1 Announce Type: cross Abstract: Artificial life systems are typically defined by a set of dynamical rules over an environment, an agent, or both, from which lifelike patterns may eme

agentsarxiv-cs-ai

Applications

LithoFormer: A Robust Framework for Stratigraphic Inference via Transformers

arXiv:2607.22804v1 Announce Type: cross Abstract: Accurate geological characterization of subsurface reservoirs from well log data is essential to support projects such as carbon capture and storage (

applicationsarxiv-cs-ai

LLM-Assisted Ontology Engineering and Construction of a French Legal Knowledge Graph

arXiv:2607.24551v1 Announce Type: new Abstract: Maintenance regulations are complex legal texts that are difficult to exploit when addressing a specific case and challenging to integrate into operatio

LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization

arXiv:2602.10576v2 Announce Type: replace-cross Abstract: Symbolic regression aims to distill mathematical equations from observational data. Recent approaches have successfully leveraged Large Langua

safetyarxiv-cs-ai

LLM-based Source Code Compression via Thresholded Symbol Ranking

arXiv:2607.24192v1 Announce Type: cross Abstract: We study the problem of lossless compression of source code, motivated by the storage demands of large-scale software archives, such as Software Herit

researcharxiv-cs-cl

LLM-Based vs. Lexicon-Based Sentiment Signals for Tail-Risk Detection in Meme Stocks

arXiv:2607.24072v1 Announce Type: new Abstract: This paper presents an empirical comparison of lexicon-based and Large Language Model (LLM)-based sentiment analysis for extracting market-relevant sign

researcharxiv-cs-cl

LLM-SoccerArena: Benchmarking LLMs on Real-World Predictions in Sports

arXiv:2607.24573v1 Announce Type: new Abstract: Large language models (LLMs) increasingly support decisions about uncertain future events, yet evaluating their ability to forecast real-world outcomes

Local Regularization Does Not Characterize Multiclass PAC Learnability

arXiv:2607.23449v1 Announce Type: new Abstract: Local regularization assigns each hypothesis a test-point-dependent score and predicts with a minimum-score hypothesis consistent with the sample. Asili

LOCKS: Page-Local Compact Key Summaries for Efficient Long-Context Decoding

arXiv:2607.24555v1 Announce Type: cross Abstract: Serving large language models at long context is bottlenecked by the key-value (KV) cache, which is read in full at every decode step. Attention keys

local-aiarxiv-cs-ai

LOCUS: Local Visual Cue Search for Enhancing Fine-Grained Perception in Multimodal Large Language Models

arXiv:2606.16586v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) remain unreliable on fine-grained visual perception, even when high-resolution inputs preserve the necessar

local-aiarxiv-cs-cv

Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data

arXiv:2607.23348v1 Announce Type: cross Abstract: Mixed continuous--categorical data pose a representation problem for continuous generative models. Flow Matching and Gaussian diffusion operate in Euc

Long-Tailed Medical Image Classification

arXiv:2607.23883v1 Announce Type: new Abstract: In this paper, we examine the difficulties of using standard techniques for medical image classification due to long-tailed distributions (wherein rarer

safetyarxiv-cs-cv

LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget

arXiv:2607.14952v3 Announce Type: replace Abstract: Long-context RL post-training is constrained by the lifetime of state and gradients, not attention cost alone. In GRPO, one multi-million-token prom

safetyarxiv-cs-lg

Looking for Affect in Spontaneous Finnish Speech through Linguistic Interpretability

model-releasesarxiv-cs-cl

arXiv:2607.24155v1 Announce Type: new Abstract: Existing research on affect in speech has shown how acoustic surface characteristics and content-related linguistic aspects of speech both relate to per

Loong: Synthesize Long Chain-of-Thoughts at Scale through Verifiers

arXiv:2509.03059v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have shown that their reasoning capabilities can be significantly improved through Reinforceme

Looping Is Not Reliability: State-Bound Evidence and Typed Revision Contracts for Agentic Code Repair

arXiv:2607.24604v1 Announce Type: cross Abstract: Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee. We study the gap between finding a c

safetyarxiv-cs-ai

LoRA for Gender-Inclusive Rewriting and Activation Steering for Counter-Narrative Generation

model-releasesarxiv-cs-cl

arXiv:2607.23083v1 Announce Type: new Abstract: Gender-inclusive language generation seeks to transform biased text into inclusive alternatives while preserving semantic meaning and contextual coheren