PPT Annotation

PPT Annotation

Rate slide presentations across systems

Step 1 of 2

Fill in your details & click Start — then pick a paper on the right

Full name Email address

Navigation: Use the ← → buttons on screen or keyboard arrow keys to navigate all presentations. Use + / − to zoom.

Please ignore while scoring: some title slides show dummy conference names or oddly formatted author names. This is intentional — do not penalize for this.

Select a paper to annotate

No papers match your search.

Do Not Answer: A Dataset for Evaluating Safeguards in LLMs

Is Human-Like Text Liked by Humans?

Reward Shaping to Mitigate Reward Hacking in RLHF

Harm or Humor: A Multimodal Multilingual Benchmark for Overt and Covert Harmful Humor

RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?

A Cognitive Writing Perspective for Constrained Long-Form Text Generation

A Fano-Style Accuracy Upper Bound for LLM Single-Pass Reasoning in Multi-Hop QA

How Fine-Tuning Objectives Shape Layer-Wise Information in LLM Hallucination Detection

HallucinationDetection

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval

Improving Long-Form Factuality via Latent LLM Steering

LongFormFactuality

IntelliAsk: Learning to Ask High-Quality Research Questions via RLVR

CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval

EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark

GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick

Visual Instruction Tuning

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Flamingo: a Visual Language Model for Few-Shot Learning

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Improved Baselines with Visual Instruction Tuning

Sigmoid Loss for Language Image Pre-Training

Learning Transferable Visual Models From Natural Language Supervision

DINOv2: Learning Robust Visual Features without Supervision

Segment Anything

Segment Anything

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Vision Transformer

High-Resolution Image Synthesis with Latent Diffusion Models

Latent Diffusion

Hierarchical Text-Conditional Image Generation with CLIP Latents

Kosmos-2: Grounding Multimodal Large Language Models to the World