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Collections including paper arxiv:2510.03215

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 14 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents

Paper • 2509.26354 • Published Sep 30 • 17

Less is More: Recursive Reasoning with Tiny Networks

Paper • 2510.04871 • Published Oct 6 • 497
Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

Paper • 2510.07499 • Published Oct 8 • 48
StreamingVLM: Real-Time Understanding for Infinite Video Streams

Paper • 2510.09608 • Published Oct 10 • 50

Open Data Synthesis For Deep Research

Paper • 2509.00375 • Published Aug 30 • 70
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training

Paper • 2509.03403 • Published Sep 3 • 22
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

Paper • 2509.03405 • Published Sep 3 • 23
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs

Paper • 2509.00930 • Published Aug 31 • 4

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Paper • 2507.19457 • Published Jul 25 • 28
Agentic Reinforced Policy Optimization

Paper • 2507.19849 • Published Jul 26 • 158
Group Sequence Policy Optimization

Paper • 2507.18071 • Published Jul 24 • 315
Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Agent Learning via Early Experience

Paper • 2510.08558 • Published Oct 9 • 266
MemMamba: Rethinking Memory Patterns in State Space Model

Paper • 2510.03279 • Published Sep 28 • 72
From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

Paper • 2509.23768 • Published Sep 28 • 48
LLMs Learn to Deceive Unintentionally: Emergent Misalignment in Dishonesty from Misaligned Samples to Biased Human-AI Interactions

Paper • 2510.08211 • Published Oct 9 • 22

Artifacts of paper "Cache-to-Cache: Direct Semantic Communication Between Large Language Models"

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
nics-efc/C2C_Fuser

Text Generation • Updated 3 days ago • 5
Sleeping

2

Cache-to-Cache Communication Demo

🔗

2

Compare Single, Text-to-Text, and Cache-to-Cache inference

about 19 hours ago

Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations

Paper • 2508.09789 • Published Aug 13 • 5
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents

Paper • 2508.13186 • Published Aug 14 • 18
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents

Paper • 2508.04038 • Published Aug 6 • 1
Prompt Orchestration Markup Language

Paper • 2508.13948 • Published Aug 19 • 48

Large Language Models

Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers

Paper • 2506.14702 • Published Jun 17 • 3
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

Paper • 2506.13585 • Published Jun 16 • 272
Scaling Test-time Compute for LLM Agents

Paper • 2506.12928 • Published Jun 15 • 63
A Survey on Latent Reasoning

Paper • 2507.06203 • Published Jul 8 • 93

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 14 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents

Paper • 2509.26354 • Published Sep 30 • 17

Agent Learning via Early Experience

Paper • 2510.08558 • Published Oct 9 • 266
MemMamba: Rethinking Memory Patterns in State Space Model

Paper • 2510.03279 • Published Sep 28 • 72
From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

Paper • 2509.23768 • Published Sep 28 • 48
LLMs Learn to Deceive Unintentionally: Emergent Misalignment in Dishonesty from Misaligned Samples to Biased Human-AI Interactions

Paper • 2510.08211 • Published Oct 9 • 22

Less is More: Recursive Reasoning with Tiny Networks

Paper • 2510.04871 • Published Oct 6 • 497
Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

Paper • 2510.07499 • Published Oct 8 • 48
StreamingVLM: Real-Time Understanding for Infinite Video Streams

Paper • 2510.09608 • Published Oct 10 • 50

Artifacts of paper "Cache-to-Cache: Direct Semantic Communication Between Large Language Models"

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97
nics-efc/C2C_Fuser

Text Generation • Updated 3 days ago • 5
Sleeping

2

Cache-to-Cache Communication Demo

🔗

2

Compare Single, Text-to-Text, and Cache-to-Cache inference

Open Data Synthesis For Deep Research

Paper • 2509.00375 • Published Aug 30 • 70
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training

Paper • 2509.03403 • Published Sep 3 • 22
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

Paper • 2509.03405 • Published Sep 3 • 23
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs

Paper • 2509.00930 • Published Aug 31 • 4

about 19 hours ago

Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations

Paper • 2508.09789 • Published Aug 13 • 5
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents

Paper • 2508.13186 • Published Aug 14 • 18
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents

Paper • 2508.04038 • Published Aug 6 • 1
Prompt Orchestration Markup Language

Paper • 2508.13948 • Published Aug 19 • 48

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Paper • 2507.19457 • Published Jul 25 • 28
Agentic Reinforced Policy Optimization

Paper • 2507.19849 • Published Jul 26 • 158
Group Sequence Policy Optimization

Paper • 2507.18071 • Published Jul 24 • 315
Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Paper • 2510.03215 • Published Oct 3 • 97

Large Language Models

Treasure Hunt: Real-time Targeting of the Long Tail using Training-Time Markers

Paper • 2506.14702 • Published Jun 17 • 3
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

Paper • 2506.13585 • Published Jun 16 • 272
Scaling Test-time Compute for LLM Agents

Paper • 2506.12928 • Published Jun 15 • 63
A Survey on Latent Reasoning

Paper • 2507.06203 • Published Jul 8 • 93

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