Search: “llm”

Where the Model Changes Its Mind: Hindsight-Divergence Localization for Efficient Reinforcement Learning with Verifiable Rewards

arXiv:2609.36864v1 Announce Type: new Abstract: Group-relative methods for reinforcement learning with verifiable rewards (RLVR) learn from differences in rollout outcomes. Independently sampling comp

30 Sept 2026

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Which Attention Heads are like the Human Head? Not the Ones that Compute

DGX agent

arXiv:2609.37991v1 Announce Type: new Abstract: Brain-AI alignment is often interpreted as a sign that model and brain perform similar computations. Whether the aligned units are causally involved in

safetyarxiv-cs-ai

30 Sept 2026

Local Ai

A Solvable Theory of Pre-training Data Poisoning: Regime-Dependent Scaling Exponents

arXiv:2609.32288v1 Announce Type: new Abstract: Pre-training data poisoning of large language models is usually studied using targeted backdoors and their survival through safety post-training, which

local-aiarxiv-cs-lg

ABC-Align: Prediction-Powered Alignment with Adaptive Bias Control

arXiv:2609.34374v1 Announce Type: new Abstract: Language model post-training is often bottlenecked by the need for human-collected preference data, which is expensive and difficult to scale. Reinforce

Tutorials

Augmenting Visual Anomaly Detection with Automated Interpretability

arXiv:2609.33818v1 Announce Type: new Abstract: Visual anomaly detectors identify deviations from known-normal data, but their anomaly signals may mix evidence of actual anomalies with benign visual v

tutorialsarxiv-cs-cv

Automated Species Identification in Camera Trap Images for Wildlife Conservation

model-releasesarxiv-cs-cv

arXiv:2609.35420v1 Announce Type: new Abstract: Wildlife conservation involves protecting, preserving, and managing wildlife species and their habitats. With today's rapid pace of human development, c

AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists

arXiv:2506.08140v2 Announce Type: replace Abstract: Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-qualit

applicationsarxiv-cs-lg

BALAR : A Bayesian Agentic Loop for Active Reasoning

arXiv:2605.05386v2 Announce Type: replace-cross Abstract: Large language models increasingly operate in interactive settings where solving a task requires multiple rounds of information exchange with

Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planning

arXiv:2609.34270v1 Announce Type: new Abstract: Interactive robot planning requires robots to infer and execute human intentions from natural language instructions that are often ambiguous, incomplete

applicationsarxiv-cs-ro

Before Answering: Evidence Sufficiency under Size-Matched Memory Construction

arXiv:2609.32269v1 Announce Type: cross Abstract: Agents that answer questions from compressed or retrieved memory must recognize when the evidence a query needs is no longer in memory. Benchmarks for

ChatGPT, how much should two companies that have collectively contributed to the economy less than $30B be worth?

ChatGPT, how much should two companies that have collectively contributed to the economy less than 30B be worth? @Lio_Cicolecchia @GaryMarcus @ey Try the following in google or ChatGPT: 'how much audi

safetygary-marcus--x

Clinical Trajectory Alignment for Medical Vision-Language Pre-training

arXiv:2609.34439v1 Announce Type: new Abstract: Medical vision-language pre-training largely follows a visit-level image-report matching paradigm, aligning paired images and reports at individual visi

Concept-Guided Fine-Tuning: Steering ViTs away from Spurious Correlations to Improve Robustness

arXiv:2603.08309v3 Announce Type: replace Abstract: Vision Transformers (ViTs) often degrade under distribution shifts because they rely on spurious correlations, such as background cues, rather than

d-OPD: Future-Aware On-Policy Distillation for Block Diffusion Language Models

arXiv:2609.35362v1 Announce Type: new Abstract: Large language models (LLMs) typically generate text autoregressively (AR), predicting one token at a time. Block diffusion language models (dLLMs) inst

Data Processing for Offline Evaluation in Recommender Systems: a Survey

arXiv:2609.31696v1 Announce Type: cross Abstract: Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on hist

researcharxiv-cs-lg

Diffusion Reward Models

arXiv:2609.33803v1 Announce Type: new Abstract: Reward models underpin the alignment of large language models, yet the dominant designs reduce each prompt--response pair to a point estimate or to a di

Local Ai

DrawingsDreamer: A Unified Multi-View Engineering Drawings Generation Model

arXiv:2609.35242v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) are essential for modern industrial Computer-Aided Design (CAD). However, existing autoregressive SVG generation models a

local-aiarxiv-cs-cv

ECG-Scroll: A Long-Horizon, Streaming Benchmark and Agent Environment for Interpretation of Ambulatory Electrocardiograms

arXiv:2609.33117v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can now interpret a standard ten-second, twelve-lead electrocardiogram (ECG) with clinically grounded, reward-v

Tutorials

Emergent One-Third Scaling Law as Attention Tries to Concentrate

arXiv:2609.32100v1 Announce Type: new Abstract: The neural scaling law relating longer training to better performance through a power law is central to today's large language models (LLMs), yet its or

tutorialsarxiv-cs-lg

Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals

arXiv:2609.32773v1 Announce Type: cross Abstract: Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured for

Google Cloud partners deliver new security agents and AI defenses with Gemini Enterprise

model-releasesgoogle-cloud-ai

As threat actors increasingly use AI to accelerate and develop cyberattacks, enterprise defenders need to rely on both AI and a critical defender’s advantage: Business context that only you possess. E

Graph Workflows in ADK: Everything You Need to Know

model-releasesgoogle-cloud-ai

Graph engineering is the design work: breaking a task into nodes, connecting them with edges, and deciding where code, models, or people control the next step. The Agent Development Kit (ADK)'s Workfl

Handwritten Text Recognition Lives in the High-Pixel Variance Subspace

model-releasesarxiv-cs-cv

arXiv:2609.35473v1 Announce Type: new Abstract: In self-supervised pretraining for Handwritten Text Recognition (HTR), pixel reconstruction methods outperform contrastive methods, unlike in natural-im

How Synthetic Labels Improve Conformal Prediction: A Perspective on Conditional Coverage

arXiv:2609.33482v1 Announce Type: new Abstract: Conformal prediction provides distribution-free finite-sample marginal coverage, but post-hoc calibration data may be too scarce to learn how uncertaint

Jev in Medicine: A Benchmark Evaluation. Preliminary Results

arXiv:2609.34024v1 Announce Type: cross Abstract: Jev is a non-generative 'System One' model that assigns probabilities to predefined answer options and cannot answer outside them. Its accuracy and ca

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

arXiv:2609.33074v1 Announce Type: new Abstract: High-performance GPU kernels are essential to modern machine learning systems, yet automatically generating kernels that are both correct and efficient

Hardware

KV-streams for Efficient Compaction in Agentic Reinforcement Learning

arXiv:2609.35750v1 Announce Type: new Abstract: Scaling the horizon of agentic LLMs is bottlenecked by the need to fit ever longer context traces in GPU memory. Context compaction has been the most po

hardwarearxiv-cs-lg

Language-Augmented Video Action Anticipation: Design Fundamentals, Benchmarks, and Open Challenges

arXiv:2609.31665v1 Announce Type: new Abstract: Action anticipation predicts future human actions from partial video under incomplete context and temporal uncertainty. Recent systems introduce large l

applicationsarxiv-cs-cv

MM-VeriRec: Failure-Guided Fusion for Verifiable Agentic Multimodal Recommendation

model-releasesarxiv-cs-cv

arXiv:2609.31718v1 Announce Type: cross Abstract: Images often carry recommendation constraints that text metadata only hints at. A movie may need to look dark, a product may need a minimal style, and

Not Every Term Adds New Structure: Sobolev Novelty for Symbolic Regression

arXiv:2609.32597v1 Announce Type: new Abstract: Symbolic regression (SR) aims to discover compact and meaningful mathematical equations from data, but searching the vast combinatorial space of symboli

On the Capability and Limitation of Hard Prompt

arXiv:2609.32302v1 Announce Type: new Abstract: Prompt engineering has become an indispensable tool for using large language models (LLMs), turning LLMs into task-specific experts without changing the

applicationsarxiv-cs-lg

OneSign: Unifying Sign Language Understanding Tasks with One Model

arXiv:2609.33090v1 Announce Type: cross Abstract: SLU encompasses a diverse set of tasks, including ISLR, CSLR, and SLT. Although these tasks share basic semantic and linguistic foundations, they are

OpenTumorBoard: A Real-World Benchmark of Multidisciplinary Tumor Board Discussion Trajectories

arXiv:2609.32810v1 Announce Type: cross Abstract: Multidisciplinary tumor boards integrate multimodal clinical observations and longitudinal patient histories through specialist discussions, yet bench

Orthogonal Witness Control for Muon Optimization via Sigmoid Spectral Reshaping

arXiv:2609.33194v1 Announce Type: new Abstract: Matrix-valued optimizers such as Muon exploit the spectral structure of neural network updates through Newton--Schulz orthogonalization, but their near-

researcharxiv-cs-lg

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c

PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks

arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha

PROACT-Agent: Progressive Runtime Oversight and Active Circuit-breaking for Real-Time Safety

arXiv:2609.34415v1 Announce Type: new Abstract: The transition from Large Language Models (LLMs) to agents shifts safety stakes from toxic text to irreversible environmental harm. While current defens

Quantifying Behavioral Tails in Black-Box Language Models

arXiv:2609.33638v1 Announce Type: new Abstract: We introduce RareTrap, a framework for estimating the probability of severe behaviors in black box large language models (LLMs). A key challenge for pro

Local Ai

RefCompose: Multi-Reference Image Generation via LoRA-Conditioned Diffusion

arXiv:2609.32389v1 Announce Type: new Abstract: Filmmakers and visual artists routinely need to compose multiple references, actors, locations, props, cultural elements, into a single coherent shot, b

local-aiarxiv-cs-cv

Agents

ReplayLens: Auditing Agents' Use of Outcomes

arXiv:2609.34177v1 Announce Type: cross Abstract: When an agent reuses logged experience, a changed decision may reflect the recorded score, the action's name, or the record's position in storage. Sta

agentsarxiv-cs-lg

ScAn-Bench: Evaluating Scaling Analysis Methodology

arXiv:2609.35707v1 Announce Type: new Abstract: Recent progress in machine learning is driven by large-scale foundation models, where scaling laws and finding optimal scaling prescriptions for archite

researcharxiv-cs-lg

SEES: A Self-Evolving Embodied System via Failure-Guided VLA Policy Adaptation

arXiv:2609.32698v1 Announce Type: new Abstract: Recent vision-language-action (VLA) policies demonstrate promising generalization across diverse short-horizon tasks. However, they remain unreliable on

safetyarxiv-cs-ro

SelfCue: Making a 3D CT Report Generator Say What It Already Knows

arXiv:2609.31788v1 Announce Type: new Abstract: Progress in 3D CT report generation is usually sought in increasingly sophisticated architectures and larger pools of training data. We find instead tha

SentZero: An Enhanced Sentence-Centric Vision-Language Pretraining for Multi-Task Zero-Shot Chest X-Ray Analysis

arXiv:2609.34479v1 Announce Type: new Abstract: Vision-language (VL) pretraining using paired chest X-ray (CXR) images and radiology reports has shown strong potential for medical image understanding.

SignFLIP: A Unified Model for Sign Language Translation and Generation via Stage-wise Alignment at Scale

arXiv:2609.35225v1 Announce Type: cross Abstract: Sign language translation and generation share the goal of bidirectional alignment between text and sign representations. However, existing approaches

Agents

SOR-Nav: Search or Relocate? Context-Gated Exploration and Cross-Region Relocation for Object Navigation

arXiv:2609.34707v1 Announce Type: new Abstract: Object navigation requires an embodied agent to find an object in an unseen environment under partial observability and a limited motion budget. Existin

agentsarxiv-cs-ro

TRACE: Expert-Aligned ECG Representation Learning with Rigorous Benchmarking and Real-World Validation in Acute Cardiac Care

arXiv:2609.34088v1 Announce Type: new Abstract: TRACE (Text-Reinforced Analysis of Cardio ECGs) is a multimodal electrocardiogram (ECG) representation model that learns clinically grounded signal embe

TSGate: Timestep-Aware Gated Attention for Diffusion Transformers

arXiv:2609.34539v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have emerged as the dominant architecture for high-fidelity image and video generation. Recent DiT systems increasingly us