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HumanDGX agent

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Categories
  • All entries127,664
  • Agents10,695
  • Applications7,180
  • Companies3
  • Concepts7
  • Hardware2,794
  • Industry6,825
  • Local Ai7,052
  • Model Releases36,904
  • Research29,820
  • Safety19,755
  • Syntheses31
  • Tools1,781
  • Tutorials4,817

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127,664Total entries
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13Categories

Knowledge catalogue

Search: “llm”

GridTimelineEvolution
22,011 results
Research

AP-BMM: Approximating Capability-Efficiency Pareto Sets of LLMs via Asynchronous Prior-guided Bayesian Model Merging

DGX agent

arXiv:2512.09972v5 Announce Type: replace-cross Abstract: Navigating the capability--efficiency trade-off in Large Language Models (LLMs) requires approximating a high-quality Pareto set. Existing mod

researcharxiv-cs-cl
28 Apr 2026
Human
DGX agent

Content type
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Model Releases

CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

DGX agent

arXiv:2509.20374v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated strong performance across general NLP tasks, but their utility in automating numerical experime

model-releasesarxiv-cs-ai
28 Apr 2026
Safety

Guided Speculative Inference for Efficient Test-Time Alignment of LLMs

DGX agent

arXiv:2506.04118v3 Announce Type: replace Abstract: We propose Guided Speculative Inference (GSI), a novel algorithm for efficient reward-guided decoding in large language models. GSI combines soft be

safetyarxiv-cs-lg
28 Apr 2026
Safety

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens

DGX agent

arXiv:2508.01191v5 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has been shown to be effective in eliciting structured reasoning (i.e., CoT reasoning) from large language models (

safetyarxiv-cs-ai
28 Apr 2026
Local Ai

Self Knowledge Re-expression: A Fully Local Method for Adapting LLMs to Tasks Using Intrinsic Knowledge

DGX agent

arXiv:2604.22939v1 Announce Type: cross Abstract: While the next-token prediction (NTP) paradigm enables large language models (LLMs) to express their intrinsic knowledge, its sequential nature constr

local-aiarxiv-cs-ai
28 Apr 2026
Safety

Thoughtful book on LLMs and linguistics — by someone who actually knows linguistics.

DGX agent

Thoughtful book on LLMs and linguistics — by someone who actually knows linguistics. Interested in the LLM vs. linguistic theory debate? My just out book will tell you (almost) all about it. https://m

safetygary-marcus--x
28 Apr 2026
Safety

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs

DGX agent

arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that

safetyarxiv-cs-ai
28 Apr 2026
Research

Scaling massive monolithic LLMs continues to yield incredible results. But to truly unlock their ceiling, the next frontier is test-time com…

DGX agent

Scaling massive monolithic LLMs continues to yield incredible results. But to truly unlock their ceiling, the next frontier is test-time compute and dynamic orchestration. Nature solves complex proble

researchdavid-ha--x
26 Apr 2026
Research

图灵奖获得者、 AI 三大教父之一的 LeCun在达沃斯的发言,算是把整个硅谷的遮羞布扯了。 他说现在整个行业都被LLM彻底洗脑了,所有人都在同一条赛道上互相挖人,谁敢偏离主流谁就被骂落后。 这也是他离开Meta的真正原因,连Meta都已经LLM-pilled,他不想再跟风了。 …

DGX agent

图灵奖获得者、 AI 三大教父之一的 LeCun在达沃斯的发言,算是把整个硅谷的遮羞布扯了。 他说现在整个行业都被LLM彻底洗脑了,所有人都在同一条赛道上互相挖人,谁敢偏离主流谁就被骂落后。 这也是他离开Meta的真正原因,连Meta都已经LLM-pilled,他不想再跟风了。 最扎心的一句话是:纯生成式架构,不管是LLM、VLM还是VLA,永远造不出哪怕猫级的智能体。 因为它们本质上只是下一个t

researchyann-lecun--x
24 Apr 2026
Model Releases

Context Is What You Need: The Maximum Effective Context Window for Real World Limits of LLMs

DGX agent

arXiv:2509.21361v2 Announce Type: replace-cross Abstract: Large language model (LLM) providers boast big numbers for maximum context window sizes. To test the real world use of context windows, we 1)

model-releasesarxiv-cs-ai
24 Apr 2026
Model Releases

Leveraging Multimodal LLMs for Built Environment and Housing Attribute Assessment from Street-View Imagery

DGX agent

arXiv:2604.21102v1 Announce Type: cross Abstract: We present a novel framework for automatically evaluating building conditions nationwide in the United States by leveraging large language models (LLM

model-releasesarxiv-cs-ai
24 Apr 2026
Research

Not-a-Bandit: Provably No-Regret Drafter Selection in Speculative Decoding for LLMs

DGX agent

arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection

researcharxiv-cs-lg
24 Apr 2026
Model Releases

Wiring the 'Why': A Unified Taxonomy and Survey of Abductive Reasoning in LLMs

DGX agent

arXiv:2604.08016v2 Announce Type: replace Abstract: Regardless of its foundational role in human discovery and sense-making, abductive reasoning--the inference of the most plausible explanation for an

model-releasesarxiv-cs-ai
24 Apr 2026
Agents

Can LLMs Infer Conversational Agent Users' Personality Traits from Chat History?

DGX agent

arXiv:2604.19785v1 Announce Type: cross Abstract: Sensitive information, such as knowledge about an individual's personality, can be can be misused to influence behavior (e.g., via personalized messag

agentsarxiv-cs-ai
23 Apr 2026
Research

Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?

DGX agent

arXiv:2502.07963v4 Announce Type: replace-cross Abstract: Medical research faces well-documented challenges in translating novel treatments into clinical practice. Publishing incentives encourage rese

researcharxiv-cs-ai
23 Apr 2026
Safety

Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction

DGX agent

arXiv:2604.19204v1 Announce Type: cross Abstract: LLMs are increasingly being considered for prediction tasks in high-stakes social service settings, but their algorithmic fairness properties in this

safetyarxiv-cs-lg
22 Apr 2026
Safety

Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs

DGX agent

arXiv:2601.15755v3 Announce Type: replace Abstract: Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an activ

safetyarxiv-cs-cl
22 Apr 2026
Model Releases

Cyber Defense Benchmark: Agentic Threat Hunting Evaluation for LLMs in SecOps

DGX agent

arXiv:2604.19533v1 Announce Type: cross Abstract: We introduce the Cyber Defense Benchmark, a benchmark for measuring how well large language model (LLM) agents perform the core SOC analyst task of th

model-releasesarxiv-cs-ai
22 Apr 2026
Safety

Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs

DGX agent

arXiv:2511.22099v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have driven major advances across domains, yet their massive size hinders deployment in resource-constrained sett

safetyarxiv-cs-ai
22 Apr 2026
Model Releases

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion

DGX agent

arXiv:2604.19015v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models (LLMs) is obstructed by a trilemma of challenges: protecting LLMs intellectual property (IP), ensuring

model-releasesarxiv-cs-ai
22 Apr 2026
Hardware

LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation

DGX agent

arXiv:2604.19167v1 Announce Type: cross Abstract: Deploying large language models (LLMs) in resource-constrained environments is hindered by heavy computational and memory requirements. We present LBL

hardwarearxiv-cs-ai
22 Apr 2026
Model Releases

CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora

DGX agent

arXiv:2604.18027v1 Announce Type: cross Abstract: Transpilation, or code translation, aims to convert source code from one programming language (PL) to another. It is beneficial for many downstream ap

model-releasesarxiv-cs-cl
21 Apr 2026
Model Releases

CoLLM: A Unified Framework for Co-execution of LLMs Federated Fine-tuning and Inference

DGX agent

arXiv:2604.16400v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly adopted in edge intelligence to power domain-specific applications and personalized services, the qua

model-releasesarxiv-cs-lg
21 Apr 2026
Model Releases

Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation

DGX agent

arXiv:2601.14590v2 Announce Type: replace Abstract: Counterfactual explanations (CFEs) provide human-centric interpretability by identifying the minimal, actionable changes required to alter a machine

model-releasesarxiv-cs-lg
21 Apr 2026
Model Releases

Emergent Misalignment via In-Context Learning: Narrow in-context examples can produce broadly misaligned LLMs

DGX agent

arXiv:2510.11288v4 Announce Type: replace Abstract: Recent work has shown that narrow finetuning can produce broadly misaligned LLMs, a phenomenon termed emergent misalignment (EM). While concerning,

model-releasesarxiv-cs-cl
21 Apr 2026
Model Releases

FedLLM: A Privacy-Preserving Federated Large Language Model for Explainable Traffic Flow Prediction

DGX agent

arXiv:2604.16612v1 Announce Type: new Abstract: Traffic prediction plays a central role in intelligent transportation systems (ITS) by supporting real-time decision-making, congestion management, and

model-releasesarxiv-cs-lg
21 Apr 2026
Model Releases

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling

DGX agent

arXiv:2604.18556v1 Announce Type: new Abstract: Weight quantization has become a standard tool for efficient LLM deployment, especially for local inference, where models are now routinely served at 2-

model-releasesarxiv-cs-cl
21 Apr 2026
Research

LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies

DGX agent

arXiv:2604.16935v1 Announce Type: cross Abstract: Scarce longitudinal evidence examines LLMs' persuasiveness and humanness along time-evolving psychological frameworks. We introduce Talk2AI, a longitu

researcharxiv-cs-lg
21 Apr 2026
Model Releases

ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition

DGX agent

arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r

model-releasesarxiv-cs-cl
21 Apr 2026
Research

The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton

DGX agent

arXiv:2510.09378v2 Announce Type: replace Abstract: Recent efforts to accelerate LLM pretraining have focused on computationally-efficient approximations that exploit second-order structure. This rais

researcharxiv-cs-lg
21 Apr 2026
Model Releases

Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs

DGX agent

arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b

model-releasesarxiv-cs-cl
20 Apr 2026
Safety

Self-Distillation as a Performance Recovery Mechanism for LLMs: Counteracting Compression and Catastrophic Forgetting

DGX agent

arXiv:2604.15794v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success, underpinning diverse AI applications. However, they often suffer from performance degra

safetyarxiv-cs-ai
20 Apr 2026
Research

Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants

DGX agent

arXiv:2604.15727v1 Announce Type: new Abstract: Large language models exhibit systematic limitations in structured logical reasoning: they conflate hypothesis generation with verification, cannot dist

researcharxiv-cs-ai
20 Apr 2026
Safety

What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context

DGX agent

arXiv:2506.02261v3 Announce Type: replace-cross Abstract: What enables large language models (LLMs) to effectively model user preferences in sequential recommendation? Our investigation reveals that e

safetyarxiv-cs-lg
20 Apr 2026
Safety

WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback

DGX agent

arXiv:2408.15549v4 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, aligning these models with human preferences has emerged as a critical challenge. Traditional a

safetyarxiv-cs-cl
20 Apr 2026
Tutorials

DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answering

DGX agent

arXiv:2604.15140v1 Announce Type: new Abstract: We introduce DiscoTrace, a method to identify the rhetorical strategies that answerers use when responding to information-seeking questions. DiscoTrace

tutorialsarxiv-cs-cl
17 Apr 2026
Safety

Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality

DGX agent

arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode

safetyarxiv-cs-cl
17 Apr 2026
Safety

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization

DGX agent

arXiv:2508.00222v5 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) has significantly advanced the complex reasoning abilities of Large Language Models (LLMs

safetyarxiv-cs-cl
16 Apr 2026
Agents

AgenticAI-DialogGen: Topic-Guided Conversation Generation for Fine-Tuning and Evaluating Short- and Long-Term Memories of LLMs

DGX agent

arXiv:2604.12179v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have improved their ability to process extended conversational contexts, yet fine-tuning and evaluat

agentsarxiv-cs-cl
15 Apr 2026
Safety

Calibration-Aware Policy Optimization for Reasoning LLMs

DGX agent

arXiv:2604.12632v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) enhances LLM reasoning but often induces overconfidence, where incorrect responses yield lower perplexity th

safetyarxiv-cs-ai
15 Apr 2026
Research

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning

DGX agent

arXiv:2409.06679v3 Announce Type: replace Abstract: Processing long contexts is increasingly important for Large Language Models (LLMs) in tasks like multi-turn dialogues, code generation, and documen

researcharxiv-cs-cl
15 Apr 2026
Safety

Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning

DGX agent

arXiv:2604.11835v1 Announce Type: cross Abstract: Machine learning for tabular data remains constrained by poor schema generalization, a challenge rooted in the lack of semantic understanding of struc

safetyarxiv-cs-ai
15 Apr 2026
Model Releases

Aligning What LLMs Do and Say: Towards Self-Consistent Explanations

DGX agent

arXiv:2506.07523v3 Announce Type: replace Abstract: Large language models (LLMs) seem to offer an easy path to interpretability: just ask them to explain their answers. Yet the features driving an ans

model-releasesarxiv-cs-cl
14 Apr 2026
Safety

Backdoors in RLVR: Jailbreak Backdoors in LLMs From Verifiable Reward

DGX agent

arXiv:2604.09748v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is an emerging paradigm that significantly boosts a Large Language Model's (LLM's) reasoning abi

safetyarxiv-cs-ai
14 Apr 2026
Research

How LLMs Might Think

DGX agent

arXiv:2604.09674v1 Announce Type: new Abstract: Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently developed an argument from rationality for the claim that LL

researcharxiv-cs-ai
14 Apr 2026
Model Releases

Persona Non Grata: Single-Method Safety Evaluation Is Incomplete for Persona-Imbued LLMs

DGX agent

arXiv:2604.11120v1 Announce Type: new Abstract: Personality imbuing customizes LLM behavior, but safety evaluations almost always study prompt-based personas alone. We show this is incomplete: prompti

model-releasesarxiv-cs-ai
14 Apr 2026
Model Releases

RL makes MLLMs see better than SFT

DGX agent

arXiv:2510.16333v2 Announce Type: replace Abstract: A dominant assumption in Multimodal Language Model (MLLM) research is that its performance is largely inherited from the LLM backbone, given its imm

model-releasesarxiv-cs-cv
14 Apr 2026
Model Releases

Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets

DGX agent

arXiv:2604.02460v2 Announce Type: replace Abstract: Recent work reports strong performance from multi-agent LLM systems (MAS), but these gains are often confounded by increased test-time computation.

model-releasesarxiv-cs-cl
14 Apr 2026
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