Papers791

The AI Hippocampus: How Far are We From Human Memory?

This survey asks how close AI memory systems are to human memory and organizes the answer into three parts: implicit memory (inside the model), explicit memory (outside storage you can look up), and agentic memory (what an AI agent keeps over time to plan and act).

#LLM memory#implicit memory#explicit memory

Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning

Intermediate

Shaotian Yan, Kaiyuan Liu et al.Jan 14arXiv

The paper introduces DASD-4B-Thinking, a small (4B) open-source reasoning model that scores like much larger models on hard math, science, and coding tests.

#sequence-level distillation#divergence-aware sampling#temperature-scheduled learning

OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG

Intermediate

Fengran Mo, Zhan Su et al.Jan 13arXiv

OpenDecoder teaches large language models (LLMs) to pay more attention to better documents during Retrieval-Augmented Generation (RAG).

#Retrieval-Augmented Generation#LLM Decoding#Attention Modulation

TranslateGemma Technical Report

Intermediate

Mara Finkelstein, Isaac Caswell et al.Jan 13arXiv

TranslateGemma is a family of open machine translation models fine-tuned from Gemma 3 to translate many languages more accurately.

#machine translation#TranslateGemma#Gemma 3

Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

Intermediate

Youwei Liu, Jian Wang et al.Jan 13arXiv

Agents often act like tourists without a map: they react to what they see now and miss long-term consequences.

#Imagine-then-Plan#world models#adaptive lookahead

3AM: 3egment Anything with Geometric Consistency in Videos

Intermediate

Yang-Che Sun, Cheng Sun et al.Jan 13arXiv

3AM is a new way to track and segment the same object across a whole video, even when the camera view changes a lot.

#video object segmentation#SAM2#geometry-aware tracking

Motion Attribution for Video Generation

Intermediate

Xindi Wu, Despoina Paschalidou et al.Jan 13arXiv

Motive is a new way to figure out which training videos teach an AI how to move things realistically, not just how they look.

#motion attribution#video diffusion#optical flow

Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge

Intermediate

Yao Tang, Li Dong et al.Jan 13arXiv

The paper introduces Multiplex Thinking, a new way for AI to think by sampling several likely next words at once and blending them into a single super-token.

#Multiplex Thinking#chain-of-thought#continuous token

Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs

Intermediate

Zhiyuan Hu, Yucheng Wang et al.Jan 13arXiv

The paper fixes a common problem in training AI reasoners: models get stuck using the same favorite solution style and stop exploring new ways to solve problems.

#Uniqueness-Aware Reinforcement Learning#LLM reasoning#strategy clustering

Parallel Context-of-Experts Decoding for Retrieval Augmented Generation

Intermediate

Giulio Corallo, Paolo PapottiJan 13arXiv

This paper introduces PCED, a way to use many documents as separate 'experts' in parallel so an AI can stitch answers together without stuffing everything into one giant prompt.

#Retrieval-Augmented Generation#PCED#contrastive decoding

VLingNav: Embodied Navigation with Adaptive Reasoning and Visual-Assisted Linguistic Memory

Intermediate

Shaoan Wang, Yuanfei Luo et al.Jan 13arXiv

VLingNav is a robot navigation system that sees, reads instructions, and acts, while deciding when to think hard and when to just move.

#Vision-Language-Action#embodied navigation#adaptive chain-of-thought

ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios

Intermediate

António Loison, Quentin Macé et al.Jan 13arXiv

ViDoRe V3 is a big, carefully built test that checks how well AI systems find and use information from both text and pictures (like tables and charts) in real documents.

#Retrieval-Augmented Generation#Multimodal RAG#Visual Document Understanding

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