Search: “llm”

SegTune: Structured and Fine-Grained Control for Song Generation

arXiv:2606.02638v1 Announce Type: cross Abstract: Recent advances in neural song generation have enabled high-quality synthesis from lyrics and global textual prompts. However, most systems fail to mo

local-aiarxiv-cs-ai

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SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory

DGX agent

arXiv:2511.16275v4 Announce Type: replace-cross Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language models (LLMs) in safety-critical scenarios, as it enables t

safetyarxiv-cs-ai

3 Jun 2026

SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition

arXiv:2606.03610v1 Announce Type: new Abstract: Skeleton-based action recognition aims to understand human behaviors from body joint sequences and is especially challenging in the one-shot setting, wh

safetyarxiv-cs-cv

Synthetic Hallucinations, Real Gains: Hard Negatives from Frontier Models for FIM Hallucination Mitigation

model-releasesarxiv-cs-lg

arXiv:2606.03130v1 Announce Type: new Abstract: Small open-source code models that power IDE autocomplete still emit hallucinated Fill-in-the-Middle (FIM) completions: syntactically natural calls to m

The Ghost Annotator: a Framework to Explore Human Label Variation in Content Moderation through Conformal Prediction

arXiv:2606.02911v1 Announce Type: new Abstract: Current research primarily focuses on model performance, while comparatively less attention has been devoted to uncertainty estimation, particularly in

safetyarxiv-cs-cl

Applications

Training-Free Multi-Concept LoRA Composition with Prompt-Aware Weighting

arXiv:2606.03792v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) successfully enables personalization in text-to-image generation by adapting pre-trained diffusion models to specific visual

applicationsarxiv-cs-cv

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection

arXiv:2606.02812v1 Announce Type: new Abstract: Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequ

agentsarxiv-cs-ai

Uber Caps Usage of AI Tools Like Claude Code to Manage Costs

model-releasessimon-willison

Uber Caps Usage of AI Tools Like Claude Code to Manage Costs I wrote the other day about Uber blowing its 2026 AI budget in four months, and how that wasn't particularly surprising given they would ha

VidMsg: A Benchmark for Implicit Message Inference in Short Videos

arXiv:2606.03635v1 Announce Type: cross Abstract: Understanding short online videos involves more than identifying visible objects and actions; video makers often include an underlying message or purp

we are seeing costs start to matter! uber just set limits of $1500 in tokens per developer per month i think we're going to start seeing mor…

we are seeing costs start to matter! uber just set limits of $1500 in tokens per developer per month i think we're going to start seeing more of this, and LangSmith Gateway is a great way to implement

agentsharrison-chase--x

When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models

arXiv:2606.03712v1 Announce Type: new Abstract: Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to graph learning tasks. By transforming graph

safetyarxiv-cs-lg

When RLHF Fails: A Mechanistic Taxonomy of Reward Hacking, Collapse, and Evaluator Gaming

arXiv:2606.03238v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) makes large-scale post-training possible by replacing an underspecified human objective with learned

local-aiarxiv-cs-ai

Why Are Linear RNNs More Parallelizable?

arXiv:2603.03612v3 Announce Type: replace-cross Abstract: The community is increasingly exploring linear RNNs (LRNNs) as language models, motivated by their expressive power and parallelizability. Whi

researcharxiv-cs-cl

A Distribution-Free Framework for Rewrite-Based Human-text Detection via Knockoff Filtering

arXiv:2606.00402v1 Announce Type: cross Abstract: We propose a distribution-free statistical framework that converts arbitrary rewrite-based detectors into detectors with finite-sample FDR guarantees

A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models

arXiv:2601.17952v2 Announce Type: replace-cross Abstract: Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer di

safetyarxiv-cs-ai

A Multi-Domain Red Teaming Framework for Safety, Robustness, and Fairness Evaluation of Medical Large Language Models

arXiv:2606.00027v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed across healthcare, yet existing benchmarks fail to capture model behavior under adversarial or

Accuracy, Stability, and Repeated-Run Reliability of Large Language Models on Deterministic Programming Tasks

arXiv:2606.00920v1 Announce Type: cross Abstract: Run-level pass rate overstates retry-free coverage by up to 17.8 percentage points -- and the gap is largest precisely for mid-performing systems. We

Tutorials

AdaptiveK: Complexity-Driven Sparse Autoencoders for Interpretable Language Model Representations

arXiv:2508.17320v3 Announce Type: replace Abstract: Understanding the internal representations of large language models (LLMs) remains a central challenge for interpretability research. Sparse autoenc

tutorialsarxiv-cs-lg

Agent Guide: A Simple Agent Behavioral Watermarking Framework

arXiv:2504.05871v3 Announce Type: replace Abstract: The increasing deployment of intelligent agents in digital ecosystems, such as social media platforms, has raised significant concerns about traceab

agentsarxiv-cs-ai

AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics

arXiv:2606.01015v1 Announce Type: cross Abstract: The convergence of Artificial Intelligence, the Internet of Things, and Robotics is no longer a futuristic vision; it is rapidly becoming the foundati

agentsarxiv-cs-ai

ARCA: Adapter-Residual Credit Assignment When Token Signals Degenerate

arXiv:2606.00257v1 Announce Type: cross Abstract: Token-level credit assignment for language-model reinforcement learning is usually formulated as if the policy were fully trainable, while practical L

ATLAS: Agentic Test-time Learning-to-Allocate Scaling

model-releasesarxiv-cs-lg

arXiv:2606.01667v1 Announce Type: new Abstract: Test-time scaling has become a major way to improve large language model reasoning, but its orchestration has remained designer-engineered: a fixed samp

b9466

local-aillama-cpp-releases

B9466 is a build release in the llama.cpp project that includes fixes and improvements to speculative decoding functionality, specifically addressing n_outputs_max issues and extracting helper functio

b9473

local-aillama-cpp-releases

B9473 is a release of llama.cpp, a C/C++ framework for large language model inference . The release represents a specific build commit from the ggml-org/llama.cpp repository. This entry likely documen

Bayesian Spectral Emotion Transition Discovery from Multi-Annotator Disagreement

arXiv:2606.01906v1 Announce Type: new Abstract: Emotions evolve through the dynamics of conversation, and understanding their transition structure is foundational to applications ranging from mental-h

Benchmarking Large Language Models for Cryptanalysis and Side-Channel Vulnerabilities

arXiv:2505.24621v3 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have transformed natural language understanding and generation, leading to extensive benchmarkin

Benchmarking Recursive-Collapse Warning Claims Under Matched False-Positive Control

model-releasesarxiv-cs-lg

arXiv:2606.00329v1 Announce Type: cross Abstract: Recursive systems can enter collapse-like regimes -- self-reinforcing amplification, persistent recursion, and narrowing diversity that mask accelerat

Beyond Procedure: Substantive Fairness in Conformal Prediction

arXiv:2602.16794v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) offers distribution-free uncertainty quantification for machine learning models, yet its interplay with fairness in

safetyarxiv-cs-lg

Hardware

Bit-Exact AI Inference Verification Without Performance Tradeoffs

arXiv:2606.00279v1 Announce Type: cross Abstract: Verifying claims about AI workloads is a pre- requisite for credible AI governance of covert adversaries (who comply with monitoring only when detecti

hardwarearxiv-cs-lg

CA-BED: Conversation-Aware Bayesian Experimental Design

arXiv:2606.01182v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at static reasoning tasks, yet their performance often degrades in interactive scenarios where information must be

Tools

California Brown Pelican

California Brown Pelican, in Fort Mason, CA, USI'm at the Microsoft Build conference today, held at Fort Mason in San Francisco. There are California Brown Pelicans diving into the water directly behi

toolssimon-willison

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

arXiv:2606.00472v1 Announce Type: cross Abstract: Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feat

Concept Heterogeneity-aware Representation Steering

arXiv:2603.02237v2 Announce Type: replace-cross Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal

Consistency evaluation of benchmarks used for causal discovery

arXiv:2606.01789v1 Announce Type: new Abstract: In graphical causal model, causal discovery aims to construct a causal graph based on numerical data and domain knowledge in plain text. However, the ev

Continual Learning involves engineering whole systems including Efficient Verifiers to make RL/fine-tuning and running evaluations much chea…

model-releasesharrison-chase--x

Continual Learning involves engineering whole systems including Efficient Verifiers to make RL/fine-tuning and running evaluations much cheaper at scale! some initial work we’re releasing from LangCha

CountGD++: Generalized Prompting for Open-World Counting

arXiv:2512.23351v2 Announce Type: replace Abstract: The flexibility and accuracy of methods for automatically counting objects in images and videos are limited by the way the object can be specified.

agentsarxiv-cs-cv

Disentangling Similarity and Relatedness in Topic Models

arXiv:2603.10619v2 Announce Type: replace Abstract: The recent success of large pre-trained language models (PLMs) has motivated their integration into topic modeling. However, PLM-augmented topic mod

Distillation of Large Language Models via Concrete Score Matching

arXiv:2509.25837v3 Announce Type: replace-cross Abstract: Large language models (LLMs) deliver remarkable performance but are costly to deploy, motivating knowledge distillation (KD) for efficient inf

DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering

arXiv:2606.01434v1 Announce Type: new Abstract: Drug-information question answering is a high-stakes setting where hallucinated facts can mislead clinical decision-making and the provenance of each ci

Efficient Exploration for Iterative Nash Preference Optimization

arXiv:2606.01382v1 Announce Type: cross Abstract: Preference alignment is central to improving large language models, but standard reward-based formulations can be restrictive when human preferences a

Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking

arXiv:2606.01240v1 Announce Type: new Abstract: The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augme

Empathy Applicability Modeling for General Health Queries

arXiv:2601.09696v2 Announce Type: replace Abstract: LLMs are increasingly being integrated into clinical workflows, yet they often lack clinical empathy, an essential aspect of effective doctor-patien

Experimenting with TPUs, GKE Managed DRANET, and Multi-cluster Inference Gateway

model-releasesgoogle-cloud-ai

What happens when your workload fails in one region but you need access to service? This is a common case for availability and uptime. With recent enhancement to the Kubernetes ecosystem and capabilit

FLaG: Fine-Grained Latent Grouping for Hallucination Detection

arXiv:2606.00301v1 Announce Type: new Abstract: Hallucinations in large language models (LLMs) arise from heterogeneous failure mechanisms, making reliable detection difficult for any single global un

researcharxiv-cs-lg

FVSpec: Real-World Property-Based Tests as Lean Challenges

arXiv:2606.01008v1 Announce Type: cross Abstract: We present a benchmark for evaluating AI models and agents on real-world formal software verification tasks. We first scrape 11,039 property-based tes

Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models

arXiv:2606.01461v1 Announce Type: new Abstract: Developing effective anticancer therapeutics remains challenging due to tumor heterogeneity and the absence of well-defined molecular targets across can

agentsarxiv-cs-lg

GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks

arXiv:2506.16114v3 Announce Type: replace-cross Abstract: Generative recommendations (GR), which usually include item tokenizers and generative Large Language Models (LLMs), have demonstrated remarkab

safetyarxiv-cs-ai

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

arXiv:2510.24081v2 Announce Type: replace Abstract: To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and