CompanyAnthropic8 recent entries5 Oct 2026Improving the Energy-Efficiency of the Code Generated by LLMs through Effective PromptingarXiv:2610.02571v1 Announce Type: cross Abstract: As AI-assisted programming becomes increasingly mainstream, the environmental impact of AI-generated software has emerged as an important consideratio→5 Oct 2026Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCIarXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f
CompanyOpenAI8 recent entries28 Sept 2026BioEVAL: A global, multi-institutional benchmark of large language and multimodal models for bioengineeringarXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing→1 Oct 2026Strong Multilingual Privacy Tagging at Encoder SpeedarXiv:2609.38630v1 Announce Type: new Abstract: Privacy redaction must remove personal information while preserving relationships expressed in text. We develop a multilingual named-entity tagger with →1 Oct 2026OGPO: One-Step Generative Policy Optimization for Real-Time Robot ControlarXiv:2601.20701v2 Announce Type: replace Abstract: Real-time robot control demands fast action generation. Diffusion and flow matching policies for robot control require multi-step sampling, limiting→1 Oct 2026Cascadia: A Control-Plane-Free Alternative to Hyperconverged AI InfrastructurearXiv:2609.38697v1 Announce Type: cross Abstract: We present Cascadia, a system for serving large language models on fleets of commodity Intel AIPCs using their CPU, integrated-GPU, and NPU resources.→2 Oct 2026Detecting Inconsistencies in Model Specifications with LLM-as-Verifier ReasoningarXiv:2610.01847v1 Announce Type: cross Abstract: Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation. Yet t→5 Oct 2026Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCIarXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f→7 Oct 2026Rethinking Visual Provenance: Detection and Watermarking Across Direct Visual Generation and LLM-Driven Code RenderingarXiv:2610.08137v1 Announce Type: cross Abstract: AI systems create images and videos with image/video generation models or by writing code and graphics descriptions that are then rendered. These rout→7 Oct 2026JEV versus LLMs: Accuracy, Cost and Calibration on Seven Political Science ReplicationsarXiv:2610.06625v2 Announce Type: replace Abstract: Large language models (LLMs) annotate and scale political text or constructs by generating text tokens. A new class of models, which TypeSafe market
CompanyGoogle8 recent entries6 Oct 2026Dynamic Harness Search: Building Multi-Agent Systems Per-Query via PredictionarXiv:2610.04137v1 Announce Type: new Abstract: Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Be→7 Oct 2026Image Bitstream Fine-grained Understanding for Privacy-Friendly AIoTarXiv:2610.08414v1 Announce Type: new Abstract: Image Bitstream Fine-grained Understanding (IBFU) aims to directly perform fine-grained classification and semantic description generation from encoded →8 Oct 2026VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence VerificationarXiv:2604.01569v2 Announce Type: replace Abstract: Video multimodal large language models achieve strong results on existing benchmarks, but answer accuracy alone does not establish whether they can →14 Oct 2026Sparse-TD-JEPA: Improving Zero-Shot Reinforcement Learning With Sparse Latent Task RepresentationsarXiv:2610.14400v1 Announce Type: new Abstract: Successor-feature-based zero-shot reinforcement learning methods pre-train a task encoder and successor-feature predictor on offline, reward-free data, →15 Oct 2026When 1+1 Backfires: Rethinking Relevance-Diversity Balancing for Sample-Aware Visual Token ReductionarXiv:2610.16615v1 Announce Type: new Abstract: Visual token compression has emerged as a critical technique for reducing the inference cost of Vision-Language Models. Existing methods select tokens b→15 Oct 2026Robota-Embed: Unified VLA Embeddings for Robot In-Context Learning and EvolutionarXiv:2610.19495v1 Announce Type: cross Abstract: Retrieving useful context for a robot requires matching its task, execution stage, and the continuation that should follow. We introduce Robota-Embed,→15 Oct 2026Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question AnsweringarXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand→15 Oct 2026Anuvani-LID: Robust and Calibrated Spoken Language Identification for Indian LanguagesarXiv:2610.20263v1 Announce Type: new Abstract: Every multilingual speech pipeline begins with a language decision, an error there propagates silently through recognition, translation and routing. In
CompanyMeta8 recent entries15 Oct 2026Open-MMUnlearning: Unifying Methods and Evaluation for MLLM UnlearningarXiv:2610.10358v2 Announce Type: replace Abstract: As multimodal large language models (MLLMs) become more capable and widely deployed, concerns about privacy and safety have become increasingly pres→15 Oct 2026Iterative Critique-Refine Framework for Enhancing LLM PersonalizationarXiv:2510.24469v2 Announce Type: replace-cross Abstract: Personalized text generation requires models not only to produce coherent text but also to align with a target user's style, tone, and topical→15 Oct 2026Genesis Steering: Better Activation Steering Through Training DataarXiv:2610.19114v1 Announce Type: new Abstract: Activation steering controls large language models at inference time, but its effectiveness depends on the choice of reference data. We introduce genesi→15 Oct 2026Energy Consumption Analysis of Discrete Diffusion and Autoregressive Language ModelsarXiv:2610.19855v1 Announce Type: new Abstract: As Large Language Models (LLMs) continue to scale, their energy consumption during inference has become a critical concern. While Autoregressive (AR) mo→15 Oct 2026D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex BackbonesarXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-→15 Oct 2026CLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation ObjectivesarXiv:2610.16876v1 Announce Type: new Abstract: Target-aware multimodal instruction selection requires useful examples and an appropriate balance of supervision. Sample-level rankings can overrepresen→15 Oct 2026Beyond Size: How Gradients Shape Pruning Decisions in Large Language ModelsarXiv:2311.04902v3 Announce Type: replace Abstract: Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting per→15 Oct 2026AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian ComputationarXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne
CompanyMistral8 recent entries7 Oct 2026Monte Carlo Estimation for KV Cache EvictionarXiv:2610.07643v1 Announce Type: cross Abstract: Most KV-cache eviction methods ask, in effect, which memory appeared important while reading the prompt? We instead ask, which memory will matter whil→9 Oct 2026Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RLarXiv:2607.16204v2 Announce Type: replace Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixe→14 Oct 2026SP^2ec: Adaptive Self-Speculative Decoding for Vision-Language ModelsarXiv:2610.18735v1 Announce Type: new Abstract: Speculative Decoding (SD) has demonstrated its efficacy in accelerating large language model inference, but for Vision-Language Models (VLMs), the diver→14 Oct 2026Soft Teacher ForcingarXiv:2610.17189v1 Announce Type: cross Abstract: Soft tokens have so far been used to replace discrete chain-of-thought in latent reasoning methods. These approaches typically require multi-stage tra→14 Oct 2026MultiAlloc: Budget-Aware Precision Allocation for KV Cache QuantizationarXiv:2610.18642v1 Announce Type: new Abstract: The Key-Value (KV) cache constitutes a dominant source of memory consumption during large language model (LLM) inference, particularly in long-context a→14 Oct 2026GA-SVD: Generation-aware Singular Value Decomposition for LLM CompressionarXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts →15 Oct 2026The Sharp Directions Are Against You: Curvature Analysis of Activation SteeringarXiv:2610.16084v1 Announce Type: new Abstract: Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for b→15 Oct 2026AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RANarXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Netw
CompanyxAI8 recent entries22 Sept 2026Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User IdentityarXiv:2609.23039v1 Announce Type: new Abstract: LLM-based AI systems answer political questions for hundreds of millions of people. Current audits measure what they say to an average user, but their b→28 Sept 2026Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior ApproacharXiv:2609.31570v1 Announce Type: cross Abstract: Deep learning has substantially accelerated the calibration of complex stochastic-volatility models, but neural point calibration alone does not captu→28 Sept 2026BioEVAL: A global, multi-institutional benchmark of large language and multimodal models for bioengineeringarXiv:2609.30489v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated historic breakthroughs in general reasoning with early successes in biomedical science. However, existing→29 Sept 2026Towards Transparent Diagnostics: Investigating Architectural Trade-offs and Explainability in Malaria DetectionarXiv:2609.31682v1 Announce Type: new Abstract: More than 80 countries have reported malaria cases with 610 thousand deaths and are projected to increase. Identifying malaria early and accurately help→1 Oct 2026Reasoning Externalization for Faithful Large Language Model Narratives of Stock Return PredictionsarXiv:2609.38869v1 Announce Type: new Abstract: In finance, interpreting machine learning predictions is essential, yet the numerical outputs of explainable AI can be difficult for non-experts to unde→1 Oct 2026DrivingBench: Can Vision-Language Models Drive a Toyota Corolla?arXiv:2609.38948v1 Announce Type: cross Abstract: Frontier models excel at many digital benchmarks, yet their ability to drive a real car, an everyday human skill, remains largely untested. We present→8 Oct 2026For Those Who Believe in Faithfulness: Optimizing the Area Under Insertion and Deletion Curves for Ranking Relative Feature ImportancearXiv:2610.09844v1 Announce Type: cross Abstract: The adoption of machine learning for socially relevant tasks requires effective explainable artificial intelligence (XAI) methods to better understand→14 Oct 2026BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained EnvironmentsarXiv:2610.15077v1 Announce Type: new Abstract: A brain tumor is an unusual growth of cells in the brain that can be cancerous or not, affecting normal brain function and causing serious risk to healt
CompanyDeepSeek8 recent entries8 Oct 2026SEER: Self-Enhancing Chain-of-Thought Compression for Reasoning ModelsarXiv:2509.14093v3 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting can substantially improve the reasoning ability of large language models (LLMs), but it often comes with high→12 Oct 2026Adaptive DHiSparse: Speculative Decoding over a Load-Adaptive KV HierarchyarXiv:2610.13708v1 Announce Type: new Abstract: Long-context serving runs out of KV memory before the hardware reaches its useful throughput. HiSparse stores history in host memory and fetches only th→14 Oct 2026MultiAlloc: Budget-Aware Precision Allocation for KV Cache QuantizationarXiv:2610.18642v1 Announce Type: new Abstract: The Key-Value (KV) cache constitutes a dominant source of memory consumption during large language model (LLM) inference, particularly in long-context a→14 Oct 2026inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMsarXiv:2610.18051v1 Announce Type: new Abstract: This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine→15 Oct 2026RECAP: Calibrating Low-Bit Reasoning Models on the History They ReadarXiv:2610.15259v1 Announce Type: new Abstract: Low-bit quantization reduces the cost of serving reasoning models but can substantially degrade long chains of thought. Each step reads cached keys and →15 Oct 2026Lingdan-V2: Large language models for clinically grounded reasoning in traditional Chinese medicinearXiv:2610.14705v1 Announce Type: cross Abstract: Large language models have advanced medical reasoning, but clinically grounded reasoning in traditional Chinese medicine (TCM) remains challenging bec→15 Oct 2026Beyond Size: How Gradients Shape Pruning Decisions in Large Language ModelsarXiv:2311.04902v3 Announce Type: replace Abstract: Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting per→15 Oct 2026AtomSearch: Evidence-Grounded Tree Search for Agent Skill OptimizationarXiv:2610.19951v1 Announce Type: new Abstract: Agent skills adapt frozen models through editable external instructions. Revising several rules at once makes changes difficult to inspect, while judgin
CompanyNVIDIA8 recent entries14 Oct 2026Stereo-Planner: Learning Stereo-to-Trajectory Planning for Zero-Shot Sim-to-Real Quadrotor NavigationarXiv:2610.15560v1 Announce Type: new Abstract: Existing navigation systems commonly rely on dedicated depth sensors or explicit depth reconstruction, while learning to generate trajectories directly →14 Oct 2026Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning PipelinearXiv:2610.14326v1 Announce Type: new Abstract: Traffic density estimation from camera feeds requires connecting visual perception with short-horizon forecasting. We present a two-stage pipeline that →14 Oct 2026InstantViR: Real-Time Video Inverse Problem Solver with Distilled Diffusion PriorarXiv:2511.14208v3 Announce Type: replace Abstract: Video inverse problems are fundamental to streaming, telepresence, and AR/VR, where high perceptual quality must coexist with tight latency constrai→14 Oct 2026AUGUstus: Autonomous Driving VLA Model with Unified Generation and UnderstandingarXiv:2610.16985v1 Announce Type: new Abstract: Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in →15 Oct 2026Robota-Embed: Unified VLA Embeddings for Robot In-Context Learning and EvolutionarXiv:2610.19495v1 Announce Type: cross Abstract: Retrieving useful context for a robot requires matching its task, execution stage, and the continuation that should follow. We introduce Robota-Embed,→15 Oct 2026Learning in Orbit: Onboard Training and Closed-Loop Attitude Control with a Thermal Segmentation Model on a SpacecraftarXiv:2610.19122v1 Announce Type: new Abstract: Deep space missions increasingly require spacecraft capable of autonomously operating in environments with communication delays and bandwidth limitation→15 Oct 2026Joint Subspace Sparse Attention for Efficient Long-Context DecodingarXiv:2610.19026v1 Announce Type: new Abstract: Sparse attention reduces the KV-cache traffic that dominates long-context LLM decoding, but practical methods largely operate at coarse granularity. Tok→15 Oct 2026Fewer Bits, More Tries: Recovering Capability Under Memory ConstraintsarXiv:2610.15372v1 Announce Type: new Abstract: Large language models are generally more capable than smaller ones, but their memory requirements can make local deployment difficult. We ask whether pa