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Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics

arXiv:2602.02343v3 Announce Type: replace-cross Abstract: Methods for controlling large language models (LLMs), including local weight fine-tuning, LoRA-based adaptation, and activation-based interven

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Model Releases

Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models

DGX agent

arXiv:2604.10079v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is the standard approach for adapting large language models (LLMs) to downstream tasks. However, we observe a persistent fa

model-releasesarxiv-cs-cl

14 Apr 2026

Woosh: A Sound Effects Foundation Model

arXiv:2604.01929v2 Announce Type: replace-cross Abstract: The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines.

Wordle 1,759 3/6 ⬛⬛⬛⬛🟨 🟨🟨🟨⬛⬛ 🟩🟩🟩🟩🟩

model-releasesanthropic--x

Anthropic's official X (Twitter) account shared a Wordle result showing the puzzle was solved in 3 out of 6 attempts for Wordle #1,759. The grid reveals the solver had no correct letters in the first

You Only Judge Once: Multi-response Reward Modeling in a Single Forward Pass

arXiv:2604.10966v1 Announce Type: cross Abstract: We present a discriminative multimodal reward model that scores all candidate responses in a single forward pass. Conventional discriminative reward m

Your Model Diversity, Not Method, Determines Reasoning Strategy

arXiv:2604.10827v1 Announce Type: new Abstract: Compute scaling for LLM reasoning requires allocating budget between exploring solution approaches (breadth) and refining promising solutions (depth). M

YUV20K: A Complexity-Driven Benchmark and Trajectory-Aware Alignment Model for Video Camouflaged Object Detection

arXiv:2604.09985v1 Announce Type: new Abstract: Video Camouflaged Object Detection (VCOD) is currently constrained by the scarcity of challenging benchmarks and the limited robustness of models agains

ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agents

arXiv:2508.04038v2 Announce Type: replace Abstract: Motion sensor time-series are central to Human Activity Recognition (HAR), yet conventional approaches are constrained to fixed activity sets and ty

4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation

arXiv:2512.17012v3 Announce Type: replace Abstract: Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4

A Benchmark of Dexterity for Anthropomorphic Robotic Hands

model-releasesarxiv-cs-ro

arXiv:2604.09294v1 Announce Type: new Abstract: Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often use

A Compact Hybrid Convolution--Frequency State Space Network for Learned Image Compression

arXiv:2511.20151v2 Announce Type: replace Abstract: Learned image compression (LIC) has recently benefited from Transformer- and state space models (SSM)- based backbones for modeling long-range depen

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

arXiv:2604.08749v1 Announce Type: new Abstract: How many of a neural network's parameters actually encode task-specific information? We investigate this question with LottaLoRA, a training paradigm in

Accelerating Local LLMs on Resource-Constrained Edge Devices via Distributed Prompt Caching

arXiv:2602.22812v2 Announce Type: replace Abstract: Since local LLM inference on resource-constrained edge devices imposes a severe performance bottleneck, this paper proposes distributed prompt cachi

Accurate and Reliable Uncertainty Estimates for Deterministic Predictions Extensions to Under and Overpredictions

arXiv:2604.08755v1 Announce Type: cross Abstract: Computational models support high-stakes decisions across engineering and science, and practitioners increasingly seek probabilistic predictions to qu

Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search

arXiv:2509.26435v2 Announce Type: replace-cross Abstract: Controllable summarization moves beyond generic outputs toward human-aligned summaries guided by specified attributes. In practice, the interd

Adaptive Rigor in AI System Evaluation using Temperature-Controlled Verdict Aggregation via Generalized Power Mean

arXiv:2604.08595v1 Announce Type: cross Abstract: Existing evaluation methods for LLM-based AI systems, such as LLM-as-a-Judge, verdict systems, and NLI, do not always align well with human assessment

Adaptive Simulation Experiment for LLM Policy Optimization

arXiv:2604.08779v1 Announce Type: new Abstract: Large language models (LLMs) have significant potential to improve operational efficiency in operations management. Deploying these models requires spec

Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning

arXiv:2512.07417v2 Announce Type: replace Abstract: Effective traffic control is essential for mitigating congestion in transportation networks. Conventional traffic management strategies, including r

AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments

arXiv:2604.06111v2 Announce Type: replace Abstract: Existing Agent benchmarks suffer from two critical limitations: high environment interaction overhead (up to 41% of total evaluation time) and imbal

Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL

arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems

arXiv:2604.08963v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remai

ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization

arXiv:2603.21180v3 Announce Type: replace Abstract: Sequential experimental design under expensive, gradient-free objectives is a central challenge in computational statistics: evaluation budgets are

AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs

arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full experimental cycle in quanti

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads

arXiv:2604.05426v2 Announce Type: replace-cross Abstract: Low-Rank Adaptation (LoRA) is now the dominant method for parameter-efficient fine-tuning of large language models, but achieving a high-quali

Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganography

arXiv:2604.09066v1 Announce Type: new Abstract: Linguistic steganography based on language models typically assumes that steganographic texts are transmitted without alteration, making them fragile to

Armageddon awaits the Senate GOP if we don’t get the SAVE America Act passed into law Let’s freaking go!

model-releaseselon-musk--x

Armageddon awaits the Senate GOP if we don’t get the SAVE America Act passed into law Let’s freaking go! McLaughlin poll released today shows 1 in 8 would-be GOP voters stay home in the midterms in ME

AssemLM: Spatial Reasoning Multimodal Large Language Models for Robotic Assembly

model-releasesarxiv-cs-ro

arXiv:2604.08983v1 Announce Type: new Abstract: Spatial reasoning is a fundamental capability for embodied intelligence, especially for fine-grained manipulation tasks such as robotic assembly. While

AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization

arXiv:2604.09445v1 Announce Type: new Abstract: Precise and real-time visual localization is critical for applications like AR/VR and robotics, especially on resource-constrained edge devices such as

AudioGuard: Toward Comprehensive Audio Safety Protection Across Diverse Threat Models

arXiv:2604.08867v1 Announce Type: cross Abstract: Audio has rapidly become a primary interface for foundation models, powering real-time voice assistants. Ensuring safety in audio systems is inherentl

Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detection

arXiv:2604.09166v1 Announce Type: new Abstract: Anomaly detection (AD) in chemical processes based on deep learning offers significant opportunities but requires large, diverse, and well-annotated tra

Automated Instruction Revision (AIR): A Structured Comparison of Task Adaptation Strategies for LLM

arXiv:2604.09418v1 Announce Type: new Abstract: This paper studies Automated Instruction Revision (AIR), a rule-induction-based method for adapting large language models (LLMs) to downstream tasks usi

BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning

arXiv:2604.09378v1 Announce Type: cross Abstract: Agent ecosystems increasingly rely on installable skills to extend functionality, and some skills bundle learned model artifacts as part of their exec

BEDTime: A Unified Benchmark for Automatically Describing Time Series

arXiv:2509.05215v3 Announce Type: replace Abstract: Recent works propose complex multi-modal models that handle both time series and language, ultimately claiming high performance on complex tasks lik

Benchmarked @DJLougen ’s Ornstein-27B-v2 Q6_K on my RTX 3090 using hermes-bench, my new open-source benchmarking UI for local LLMs and Herme…

model-releasesclem-delangue--x

Benchmarked @DJLougen ’s Ornstein-27B-v2 Q6_K on my RTX 3090 using hermes-bench, my new open-source benchmarking UI for local LLMs and Hermes agents. Ornstein is a Qwen 3.5 27B fine-tune trained on re

Benchmarking CNN- and Transformer-Based Models for Surgical Instrument Segmentation in Robotic-Assisted Surgery

arXiv:2604.09151v1 Announce Type: new Abstract: Accurate segmentation of surgical instruments in robotic-assisted surgery is critical for enabling context-aware computer-assisted interventions, such a

Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer

arXiv:2604.09414v1 Announce Type: cross Abstract: Learning-to-Defer routes each input to the expert that minimizes expected cost, but it assumes that the information available to every expert is fixed

Bharat Scene Text: A Novel Comprehensive Dataset and Benchmark for Indian Language Scene Text Understanding

arXiv:2511.23071v2 Announce Type: replace-cross Abstract: Reading scene text, that is, text appearing in images, has numerous application areas, including assistive technology, search, and e-commerce.

Biologically-Grounded Multi-Encoder Architectures as Developability Oracles for Antibody Design

arXiv:2604.09369v1 Announce Type: cross Abstract: Generative models can now propose thousands of de novo antibody sequences, yet translating these designs into viable therapeutics remains constrained

Boosting Brain-inspired Path Integration Efficiency via Learning-based Replication of Continuous Attractor Neurodynamics

arXiv:2511.17687v2 Announce Type: replace Abstract: The brain's Path Integration (PI) mechanism offers substantial guidance and inspiration for Brain-Inspired Navigation (BIN). However, the PI capabil

'Both the utopia and apocalypse scenarios ignore AI's limitations.' Prof. Yoav Shoham, one of the world's leading artificial intelligence re…

model-releasesai21-labs--x

'Both the utopia and apocalypse scenarios ignore AI's limitations.' Prof. Yoav Shoham, one of the world's leading artificial intelligence researchers and founder of @AI21Labs, discusses hype cycles, u

Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models

arXiv:2604.08964v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently become a promising alternative to autoregressive large language models (ARMs). Semi-autoregressive

CAD 100K: A Comprehensive Multi-Task Dataset for Car Related Visual Anomaly Detection

arXiv:2604.09023v1 Announce Type: new Abstract: Multi-task visual anomaly detection is critical for car-related manufacturing quality assessment. However, existing methods remain task-specific, hinder

CatalogStitch: Dimension-Aware and Occlusion-Preserving Object Compositing for Catalog Image Generation

arXiv:2604.08836v1 Announce Type: new Abstract: Generative object compositing methods have shown remarkable ability to seamlessly insert objects into scenes. However, when applied to real-world catalo

China has erased the US lead in AI, Stanford HAI’s 2026 AI index reveals

model-releasessiliconangle

Stanford University researchers today released their highly anticipated 2026 AI Index Report, revealing a global landscape where artificial intelligence technology is being adopted at record-breaking

Claude code skill for neurotech/BCI machine learning [P]

model-releasesr-machinelearning

This r/MachineLearning post discusses a Claude Code skill tailored for neurotechnology and brain-computer interface (BCI) machine learning workflows, likely covering domain-specific tasks such as neur

Cluster-First Labelling: An Automated Pipeline for Segmentation and Morphological Clustering in Histology Whole Slide Images

arXiv:2604.09370v1 Announce Type: cross Abstract: Labelling tissue components in histology whole slide images (WSIs) is prohibitively labour-intensive: a single slide may contain tens of thousands of

Compositional-Degradation UAV Image Restoration: Conditional Decoupled MoE Network and A Benchmark

arXiv:2604.09313v1 Announce Type: cross Abstract: UAV images are critical for applications such as large-area mapping, infrastructure inspection, and emergency response. However, in real-world flight

CONDESION-BENCH: Conditional Decision-Making of Large Language Models in Compositional Action Space

arXiv:2604.09029v1 Announce Type: cross Abstract: Large language models have been widely explored as decision-support tools in high-stakes domains due to their contextual understanding and reasoning c